diff --git a/.github/workflows/mcb7-unified-runner-checks.yml b/.github/workflows/mcb7-unified-runner-checks.yml
index ffc4c025..7bcffe4b 100644
--- a/.github/workflows/mcb7-unified-runner-checks.yml
+++ b/.github/workflows/mcb7-unified-runner-checks.yml
@@ -65,6 +65,7 @@ jobs:
           OPENAI_API_KEY: ci-placeholder
           MINICPM_API_KEY: ci-placeholder
           TYPESAFE_API_KEY: ci-placeholder
+          GEMINI_API_KEY: ci-placeholder
         run: |
           uv run model-bench models
           uv run model-bench tasks
diff --git a/experiments/model-capability-benchmark/HOW_TO_USE.md b/experiments/model-capability-benchmark/HOW_TO_USE.md
index eb7cc72a..c3b28b93 100644
--- a/experiments/model-capability-benchmark/HOW_TO_USE.md
+++ b/experiments/model-capability-benchmark/HOW_TO_USE.md
@@ -501,6 +501,99 @@ benchmark semantics. Start a new campaign/run instead.
 
 ## 12. Run all five core verticals for one model
 
+### Consolidate runs by latest sample attempt
+
+`model-bench consolidate` writes a new immutable run from existing evidence,
+without inference. Repeat `--run-dir` for every base/recovery run to include:
+
+```bash
+uv run model-bench consolidate \
+  --run-dir results/runs/base-run \
+  --run-dir results/runs/recovery-run \
+  --run-id model-consolidated-v1 \
+  --run-group model-consolidated \
+  --plan-only
+```
+
+Remove `--plan-only` to materialize the snapshot and report. The output must not
+exist: use a new run ID for each new consolidation. Add all five base capability
+runs to retain a complete model result, then include recovery runs as additional
+sources. The source directory order does not affect selection.
+
+The logical key includes model, capability, dataset revision/split, sample ID,
+task version, prompt version and suite version. Selection uses the latest state
+timestamp; ties use source run ID, attempt and case ID in that order. A newer
+invalid result replaces an older valid result. Inference and evaluation are copied
+from the same attempt. No latest incomplete/failed attempt without paired evidence
+is silently dropped or replaced by an older success: consolidate rejects it and
+requires recovery first. Profiles, seeds, artifacts and dataset/task definitions
+must be compatible. Sources are checksumed before and after reading.
+
+Each selected case retains its original run/case/attempt, generation settings,
+timestamp and benchmark/runtime signatures. Aggregate metrics are recalculated on
+the deduplicated cases; original runs are untouched. Mixed generation budgets are
+explicit in the manifest and dashboard. Consolidated benchmark signatures are
+separate from uniform-budget comparisons. Hardware/resource evidence is not
+attributed to a single new execution of the consolidated cases.
+
+```bash
+uv run model-bench project --rebuild --export-dashboard
+uv run model-bench dashboard-build
+```
+
+Dashboard exports default to `--result-view latest`: the newest completed
+consolidated result replaces the base cells for that model/capability/profile;
+other models keep their ordinary CURRENT cells. Recovery subsets alone never
+replace complete results. Consolidated runs are labeled in the dashboard.
+To inspect only ordinary uniform-configuration results instead:
+
+```bash
+uv run model-bench dashboard-data --result-view standard
+uv run model-bench dashboard-build
+```
+
+The canonical SQL views `v_current_quality_results` and
+`v_current_performance_results` remain restricted to standard runs. The dashboard's
+latest selection is separately exposed as `v_latest_quality_results`.
+
+### Recover only invalid or failed cases with a different output budget
+
+Use `--rerun-errors-from` to select unsuccessful latest cases from a previous run.
+This includes `completed` cases whose evaluation has `valid=false`, as well as
+pipeline `failed` cases. Unlike `--retry-failures`, this creates a separate recovery
+experiment and can change the token budget. A newer valid result for the same
+model/capability/dataset/sample supersedes an earlier invalid result in the source
+evidence. Repeat the source option to combine multiple run directories.
+
+```bash
+export BENCHMARK_TIMEOUT_SECONDS=180
+
+uv run model-bench run \
+  --models "$MODEL" \
+  --capabilities structured-output \
+  --profile core \
+  --run-group "${CAMPAIGN}-recovery-4096" \
+  --run-id "${CAMPAIGN}-${MODEL}-structured-output-recovery-4096" \
+  --rerun-errors-from "results/runs/${CAMPAIGN}-${MODEL}-structured-output-core" \
+  --max-output-tokens 4096 \
+  --plan-only
+```
+
+Remove `--plan-only` to execute the selection. The preview does not contact a
+provider or create output files. Keep the source profile and seed; requested samples
+must still exist in the current dataset selection. Use a new run ID and output
+directory. Recovery manifests record source run IDs, state checksums, selected
+logical cases and the generation override; the original evidence is untouched.
+Repeating the same recovery command resumes it. If selection or token override
+changes, use another new run ID.
+
+Recovery runs remain available in history but are excluded from canonical CURRENT
+selection. Their scores measure recovery on an error-selected subset, not quality
+on the complete benchmark. The existing `BENCHMARK_TIMEOUT_SECONDS` environment
+variable controls provider request timeouts; more output tokens alone do not raise
+the timeout. `--max-output-tokens` also works for ordinary full runs without editing
+the shared suite configuration.
+
 After you are comfortable running the first vertical manually:
 
 ~~~bash
@@ -551,6 +644,55 @@ uv run model-bench dashboard-build
 
 ## 14. Move to the next model
 
+### One public JSON file for every dashboard view
+
+Every dashboard export automatically replaces
+`results/published/dashboard-data.json`. This is a single, versioned bundle with
+`overview`, `capabilities`, `models` and `runs` maps: all routes, including frontier
+and sensitivity (inside overview), can use the same snapshot. `generated_at_utc`
+identifies when it was exported. The source is the selected analytics view, so
+consolidated results and their mixed-budget labels are retained.
+
+Both commands refresh the public bundle automatically:
+
+```bash
+uv run model-bench project --export-dashboard
+uv run model-bench dashboard-data
+```
+
+The bundle is serialized completely and then atomically replaces the previous file.
+Failed exports preserve the previous public file. Only files referenced by the
+current export index are included; stale files are excluded. Known credential fields
+and local filesystem paths are redacted, including serialized event metadata.
+The original internal per-view exports remain available for local analysis.
+
+Host this file at a stable URL, for example `/data/dashboard-data.json`. To make the
+existing dashboard load all views dynamically, set this **before** its module script:
+
+```html
+<script>window.__MCB_DATA_URL__ = '/data/dashboard-data.json';</script>
+```
+
+The application fetches once on startup with `cache: 'no-store'`, validates the
+bundle envelope and initializes every route from it. A load error is displayed
+explicitly, without falling back to fixture data. Existing embedded/offline builds
+continue to work when no URL is configured. An external page can also consume it:
+
+```javascript
+const response = await fetch('/data/dashboard-data.json', { cache: 'no-store' });
+if (!response.ok) throw new Error(`Dashboard data: HTTP ${response.status}`);
+const snapshot = await response.json();
+const leaderboard = snapshot.overview.decision.model_summaries;
+const capabilities = snapshot.capabilities;
+const models = snapshot.models;
+const runs = snapshot.runs;
+```
+
+Updating the local bundle does not upload it: the hosting/deployment pipeline must
+sync `results/published/dashboard-data.json` to that URL. Serve JSON with compression
+and, if hosted on a different origin, appropriate CORS headers. Reloading the page
+loads the current snapshot; already-open pages do not poll automatically.
+
 Example:
 
 ~~~bash
diff --git a/experiments/model-capability-benchmark/README.md b/experiments/model-capability-benchmark/README.md
index c89ed934..e90a2e43 100644
--- a/experiments/model-capability-benchmark/README.md
+++ b/experiments/model-capability-benchmark/README.md
@@ -165,9 +165,21 @@ New runs are stored by default under `results/runs/<run-id>`, while `run_group`
 Korgis model residency is managed through its admin API; the Korgis server process itself
 is intentionally external to this benchmark.
 
+`model-bench consolidate` creates an immutable latest-attempt result from base and
+recovery runs, deduplicating logical samples and recalculating metrics without
+inference. Dashboard exports prefer explicitly consolidated results by default and
+label mixed budgets; `--result-view standard` retains the uniform-configuration
+CURRENT view. Source evidence is preserved. See [the consolidation runbook](HOW_TO_USE.md#consolidate-runs-by-latest-sample-attempt).
+
 See `MCB_7_UNIFIED_RUNNER.md` for architecture, failure semantics and the controlled
 real-provider validation runbook.
 
+Dashboard exports also atomically update `results/published/dashboard-data.json`,
+a public bundle containing every view's data. Set `window.__MCB_DATA_URL__` before
+loading the dashboard to fetch that single file from a stable hosting URL.
+See [the public-data runbook](HOW_TO_USE.md#one-public-json-file-for-every-dashboard-view)
+for the schema, automatic refresh commands and hosting setup.
+
 ## Capability report
 
 Every run now produces a neutral capability × model report without an overall score or
diff --git a/experiments/model-capability-benchmark/dashboard/package.json b/experiments/model-capability-benchmark/dashboard/package.json
index ab38a56b..5c7baa3f 100644
--- a/experiments/model-capability-benchmark/dashboard/package.json
+++ b/experiments/model-capability-benchmark/dashboard/package.json
@@ -10,7 +10,8 @@
     "preview": "vite preview",
     "test:compare": "node --experimental-strip-types --test src/components/compareThreeLogic.test.ts src/components/hardwareEvidence.test.ts src/components/compareCockpitLogic.test.ts",
     "test:frontier": "node --experimental-strip-types --test src/components/frontierSelection.test.ts",
-    "test:guide": "node --experimental-strip-types --test src/datasetGuideData.test.ts"
+    "test:guide": "node --experimental-strip-types --test src/datasetGuideData.test.ts",
+    "test:bundle": "node --experimental-strip-types --test src/dashboardBundle.test.ts"
   },
   "dependencies": {
     "lucide-react": "^1.47.0",
diff --git a/experiments/model-capability-benchmark/dashboard/src/components/Shell.tsx b/experiments/model-capability-benchmark/dashboard/src/components/Shell.tsx
index 8cbd8c8d..b5804b40 100644
--- a/experiments/model-capability-benchmark/dashboard/src/components/Shell.tsx
+++ b/experiments/model-capability-benchmark/dashboard/src/components/Shell.tsx
@@ -13,6 +13,7 @@ import {
   TrendingUp,
 } from 'lucide-react';
 import type { ReactNode } from 'react';
+import { overview } from '../data';
 import { navigate, usePathname } from '../router';
 
 function Link({
@@ -123,7 +124,20 @@ export function Shell({ children }: { children: ReactNode }) {
           </span>
         </div>
       </aside>
-      <main className="app-content">{children}</main>
+      <main className="app-content">
+        {overview.consolidations?.length ? (
+          <div className="fixture-banner" role="status">
+            Consolidated results · latest attempt per sample ·
+            {overview.consolidations.some((row) => row.generation_policy.mixed_generation)
+              ? ' mixed generation budgets; not a uniform-budget comparison. '
+              : ' combined source runs. '}
+            {[...new Set(overview.consolidations.map((row) => row.run_id))].map((runId) => (
+              <Link key={runId} href={`/runs/${encodeURIComponent(runId)}`}>{runId} </Link>
+            ))}
+          </div>
+        ) : null}
+        {children}
+      </main>
     </div>
   );
 }
diff --git a/experiments/model-capability-benchmark/dashboard/src/dashboardBundle.test.ts b/experiments/model-capability-benchmark/dashboard/src/dashboardBundle.test.ts
new file mode 100644
index 00000000..7f02c1d2
--- /dev/null
+++ b/experiments/model-capability-benchmark/dashboard/src/dashboardBundle.test.ts
@@ -0,0 +1,21 @@
+import assert from 'node:assert/strict';
+import test from 'node:test';
+import { parseDashboardBundle } from './dashboardBundle.ts';
+
+const valid = {
+  schema_version: '1', generated_at_utc: '2026-10-22T00:00:00Z',
+  overview: { models: [], capabilities: [], cells: [], runs: [] },
+  capabilities: { cap: {} }, models: { model: {} }, runs: { run: {} },
+};
+
+test('accepts one snapshot containing all route maps', () => {
+  assert.equal(parseDashboardBundle(valid), valid);
+});
+
+test('rejects unsupported, missing or malformed route data', () => {
+  for (const invalid of [null, {}, { ...valid, schema_version: '2' },
+    { ...valid, models: [] }, { ...valid, runs: null }, { ...valid, capabilities: { cap: 'bad' } },
+    { ...valid, overview: { ...valid.overview, cells: 'bad' } }]) {
+    assert.throws(() => parseDashboardBundle(invalid), /Unsupported or incomplete/);
+  }
+});
diff --git a/experiments/model-capability-benchmark/dashboard/src/dashboardBundle.ts b/experiments/model-capability-benchmark/dashboard/src/dashboardBundle.ts
new file mode 100644
index 00000000..bc31e1a5
--- /dev/null
+++ b/experiments/model-capability-benchmark/dashboard/src/dashboardBundle.ts
@@ -0,0 +1,19 @@
+import type { DashboardBundle } from './types';
+
+function record(value: unknown): value is Record<string, unknown> {
+  return typeof value === 'object' && value !== null && !Array.isArray(value);
+}
+
+export function parseDashboardBundle(value: unknown): DashboardBundle {
+  if (!record(value) || value.schema_version !== '1' || typeof value.generated_at_utc !== 'string'
+    || !record(value.overview)) {
+    throw new Error('Unsupported or incomplete dashboard data file');
+  }
+  const overview = value.overview;
+  if (!['models', 'capabilities', 'cells', 'runs'].every((key) => Array.isArray(overview[key]))
+    || !['capabilities', 'models', 'runs'].every((key) => record(value[key])
+      && Object.values(value[key]).every(record))) {
+    throw new Error('Unsupported or incomplete dashboard data file');
+  }
+  return value as unknown as DashboardBundle;
+}
diff --git a/experiments/model-capability-benchmark/dashboard/src/data.ts b/experiments/model-capability-benchmark/dashboard/src/data.ts
index 6ee76afc..d4b4fa5e 100644
--- a/experiments/model-capability-benchmark/dashboard/src/data.ts
+++ b/experiments/model-capability-benchmark/dashboard/src/data.ts
@@ -2,6 +2,7 @@ import overviewFixture from './data/overview.fixture.json';
 import capabilityFixture from './data/structured-output.fixture.json';
 import type {
   CapabilityPayload,
+  DashboardBundle,
   ModelPayload,
   OverviewPayload,
   RunPayload,
@@ -9,6 +10,8 @@ import type {
 
 declare global {
   interface Window {
+    __MCB_DATA_URL__?: string;
+    __MCB_DASHBOARD_DATA__?: DashboardBundle;
     __MCB_OVERVIEW__?: OverviewPayload;
     __MCB_CAPABILITY__?: CapabilityPayload;
     __MCB_CAPABILITIES__?: Record<string, CapabilityPayload>;
@@ -18,15 +21,17 @@ declare global {
 }
 
 export const overview =
-  (window.__MCB_OVERVIEW__ ?? overviewFixture) as OverviewPayload;
+  (window.__MCB_DASHBOARD_DATA__?.overview ?? window.__MCB_OVERVIEW__ ?? overviewFixture) as OverviewPayload;
 
 export const capability =
-  (window.__MCB_CAPABILITY__ ?? capabilityFixture) as CapabilityPayload;
+  (window.__MCB_DASHBOARD_DATA__?.capabilities['structured-output']
+    ?? Object.values(window.__MCB_DASHBOARD_DATA__?.capabilities ?? {})[0]
+    ?? window.__MCB_CAPABILITY__ ?? capabilityFixture) as CapabilityPayload;
 
 export const capabilityPayloads: Record<string, CapabilityPayload> =
-  window.__MCB_CAPABILITIES__ ?? {
+  window.__MCB_DASHBOARD_DATA__?.capabilities ?? window.__MCB_CAPABILITIES__ ?? {
     [capability.capability_id]: capability,
   };
 
-export const modelPayloads = window.__MCB_MODELS__ ?? {};
-export const runPayloads = window.__MCB_RUNS__ ?? {};
+export const modelPayloads = window.__MCB_DASHBOARD_DATA__?.models ?? window.__MCB_MODELS__ ?? {};
+export const runPayloads = window.__MCB_DASHBOARD_DATA__?.runs ?? window.__MCB_RUNS__ ?? {};
diff --git a/experiments/model-capability-benchmark/dashboard/src/main.tsx b/experiments/model-capability-benchmark/dashboard/src/main.tsx
index ed3b67f5..34a0261e 100644
--- a/experiments/model-capability-benchmark/dashboard/src/main.tsx
+++ b/experiments/model-capability-benchmark/dashboard/src/main.tsx
@@ -1,10 +1,23 @@
 import { StrictMode } from 'react';
 import { createRoot } from 'react-dom/client';
-import { App } from './App';
+import { parseDashboardBundle } from './dashboardBundle';
 import './styles.css';
 
-createRoot(document.getElementById('root')!).render(
-  <StrictMode>
-    <App />
-  </StrictMode>,
-);
+async function start() {
+  if (window.__MCB_DATA_URL__) {
+    const response = await fetch(window.__MCB_DATA_URL__, { cache: 'no-store' });
+    if (!response.ok) throw new Error(`Dashboard data: HTTP ${response.status}`);
+    window.__MCB_DASHBOARD_DATA__ = parseDashboardBundle(await response.json());
+  }
+  // Import after loading data: every route uses the same complete snapshot.
+  const { App } = await import('./App');
+  createRoot(document.getElementById('root')!).render(
+    <StrictMode><App /></StrictMode>,
+  );
+}
+
+start().catch((error: unknown) => {
+  const root = document.getElementById('root')!;
+  root.setAttribute('role', 'alert');
+  root.textContent = error instanceof Error ? error.message : 'Unable to load dashboard data';
+});
diff --git a/experiments/model-capability-benchmark/dashboard/src/pages/ExecutivePages.tsx b/experiments/model-capability-benchmark/dashboard/src/pages/ExecutivePages.tsx
index a3675545..b563a65b 100644
--- a/experiments/model-capability-benchmark/dashboard/src/pages/ExecutivePages.tsx
+++ b/experiments/model-capability-benchmark/dashboard/src/pages/ExecutivePages.tsx
@@ -1221,7 +1221,7 @@ function ReliabilityBars({ models }: { models: DecisionModelSummary[] }) {
         return (
           <div className={tiedBest ? 'executive-reliability-row best' : 'executive-reliability-row'} key={model.model_signature}>
             <div>
-              <strong>{model.model_key}</strong>
+              <strong>{model.model_key}{model.result_policy === 'consolidated-latest-attempt' ? ' · consolidated' : ''}</strong>
               <span className="executive-model-meta">
                 <span>{model.quality_coverage_complete ? 'Complete quality coverage' : 'Partial quality coverage'}</span>
                 <RuntimeBadge model={model} compact />
diff --git a/experiments/model-capability-benchmark/dashboard/src/types.ts b/experiments/model-capability-benchmark/dashboard/src/types.ts
index 5dd074ac..e4951b6f 100644
--- a/experiments/model-capability-benchmark/dashboard/src/types.ts
+++ b/experiments/model-capability-benchmark/dashboard/src/types.ts
@@ -90,6 +90,7 @@ export interface QualityPolicy {
 }
 
 export interface DecisionModelSummary extends DashboardModel {
+  result_policy?: 'standard' | 'consolidated-latest-attempt';
   quality_policy_id: string;
   overall_quality_score: number | null;
   quality_coverage_capabilities: number;
@@ -280,6 +281,13 @@ export interface SensitivityPayload {
 
 export interface OverviewPayload {
   schema_version: string;
+  result_view?: 'latest' | 'standard';
+  consolidations?: Array<{
+    run_id: string;
+    model_key: string;
+    capability_id: string;
+    generation_policy: { mixed_generation?: boolean; generation_configs?: unknown[] };
+  }>;
   fixture?: boolean;
   models: DashboardModel[];
   capabilities: string[];
@@ -290,6 +298,15 @@ export interface OverviewPayload {
   sensitivity?: SensitivityPayload;
 }
 
+export interface DashboardBundle {
+  schema_version: '1';
+  generated_at_utc: string;
+  overview: OverviewPayload;
+  capabilities: Record<string, CapabilityPayload>;
+  models: Record<string, ModelPayload>;
+  runs: Record<string, RunPayload>;
+}
+
 export interface FamilyBreakdown {
   model_key: string;
   family: string;
diff --git a/experiments/model-capability-benchmark/models.yaml b/experiments/model-capability-benchmark/models.yaml
index 2e6add30..dbfd8f34 100644
--- a/experiments/model-capability-benchmark/models.yaml
+++ b/experiments/model-capability-benchmark/models.yaml
@@ -144,6 +144,19 @@ runtimes:
 
 
 models:
+  lfm2.5-24b-a2b-ud-q3-k-xl:
+    model_id: unsloth/LFM2.5-24B-A2B-GGUF
+    runtime_model_id: lfm2.5-24b-a2b-ud-q3-k-xl
+    runtime: korgis-local
+    family: lfm2.5
+    parameters_b: 24
+    artifact:
+      format: gguf
+      quantization: UD-Q3_K_XL
+      metadata:
+        resolved_by: korgis-model-registry
+    tags: [local, open-weight, moe]
+
   qwen3.5-0.8b-q4km:
     model_id: unsloth/qwen3.5-0.8b
     runtime_model_id: qwen3.5-0.8b-q4km
diff --git a/experiments/model-capability-benchmark/results/published/dashboard-data.json b/experiments/model-capability-benchmark/results/published/dashboard-data.json
new file mode 100644
index 00000000..c8b949ac
--- /dev/null
+++ b/experiments/model-capability-benchmark/results/published/dashboard-data.json
@@ -0,0 +1 @@
+{"capabilities":{"intent-classification":{"benchmark_signatures":["sha256:benchmark:718e761e4ba3410c289a5bba91a6474827caaa8da30e644b3df925ba4d16fbfc","sha256:benchmark:9ed670e7bf347a304b5a8e0f66561d1ef0fa44378a6ac03e3a663272121c3f0b","sha256:consolidated:42ab94943101512840504e431240a2dc1e9c2c51d6e055498c7b6b44c803f515"],"capability_id":"intent-classification","cases":[],"cells":[{"artifact_format":"gguf","artifact_size_bytes":null,"benchmark_signature":"sha256:benchmark:9ed670e7bf347a304b5a8e0f66561d1ef0fa44378a6ac03e3a663272121c3f0b","capability_id":"intent-classification","comparison_metric":"accuracy","completed_at_utc":"2026-10-06T10:03:19.101787+00:00","deployment":"local","effective_model_id":"bonsai-27b-q10","execution_signature":"sha256:execution:7af693b03b87a55605b1c7c43daf0f7e8b6e2ab607b934628d5d633f8f38f67b","experiment_kind":"standard","failure_count":0,"family":null,"generation_policy":{},"git_commit":"08bbb92824f3070d93fb3c16b5847b46dec03dfb","model_id":"prism-ml/bonsai-27b","model_key":"bonsai-27b-q10","model_signature":"sha256:model:fa0bee720418b717e2a5ae34c60712580c9e9d17c6ce62d3a2cbb639ae08d15d","parameters_b":null,"practical_delta":0.03,"primary_metric":"accuracy","primary_value":0.5974025974025974,"profile":"core","provider_key":"korgis","quantization":"Q1_0","resource_summary":{"accelerator_memory_bytes_peak":null,"capability_id":"intent-classification","execution_signature":"sha256:execution:7af693b03b87a55605b1c7c43daf0f7e8b6e2ab607b934628d5d633f8f38f67b","model_key":"bonsai-27b-q10","process_cpu_percent_avg":4.141997751956015,"process_rss_bytes_avg":5899303355.703257,"process_rss_bytes_peak":10491068416.0,"run_id":"2026-10-core-v1-bonsai-27b-q10-intent-classification-core","sample_count":4416,"sample_interval_ms":317.0853588508965,"sampling_error_count":0,"scope":"owned_backend_process","source":"[redacted 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\"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"started","timestamp_utc":"2026-10-13T11:43:08.227185+00:00"},{"attempt":null,"capability_id":null,"case_id":null,"dataset_id":null,"duration_ms":4096.867709013168,"error_message":null,"error_type":null,"event_id":"9d89d27b-f4be-45bc-9911-daa46058e9e8","event_type":"model.prepare.completed","metadata_json":"{\"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"provider_key\": \"korgis\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_execution_metadata\": {\"artifact_size_bytes\": 4121781472, \"backend\": \"llama_server\", \"quantization\": \"UD-Q2_K_XL\", \"runtime_config\": {\"backend\": \"llama_server\", \"ctx_size\": 8192, \"enable_thinking\": false, \"flash_attn\": true, \"max_kv_size\": null, \"n_batch\": 512, \"n_gpu_layers\": 0, \"n_threads\": 8, \"n_ubatch\": 512, \"offload_kqv\": true, \"show_thinking\": false, \"timeout\": 1200, \"use_mmap\": true}, \"runtime_key\": \"qwen3.5-9b-ud-q2kxl\", \"runtime_source\": \"korgis\"}, \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"completed","timestamp_utc":"2026-10-13T11:43:12.324496+00:00"},{"attempt":null,"capability_id":"structured-output","case_id":null,"dataset_id":null,"duration_ms":null,"error_message":null,"error_type":null,"event_id":"63c7efd9-dadd-40c4-b758-ea87de608901","event_type":"capability.loading.started","metadata_json":"{\"capability_id\": \"structured-output\", \"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"provider_key\": \"korgis\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_execution_metadata\": {\"artifact_size_bytes\": 4121781472, \"backend\": \"llama_server\", \"quantization\": \"UD-Q2_K_XL\", \"runtime_config\": {\"backend\": \"llama_server\", \"ctx_size\": 8192, \"enable_thinking\": false, \"flash_attn\": true, \"max_kv_size\": null, \"n_batch\": 512, \"n_gpu_layers\": 0, \"n_threads\": 8, \"n_ubatch\": 512, \"offload_kqv\": true, \"show_thinking\": false, \"timeout\": 1200, \"use_mmap\": true}, \"runtime_key\": \"qwen3.5-9b-ud-q2kxl\", \"runtime_source\": \"korgis\"}, \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"started","timestamp_utc":"2026-10-13T11:43:12.324788+00:00"},{"attempt":null,"capability_id":"structured-output","case_id":null,"dataset_id":null,"duration_ms":null,"error_message":null,"error_type":null,"event_id":"dc98760f-de53-4e6d-9517-ef6206b10029","event_type":"capability.started","metadata_json":"{\"benchmark_signature\": \"sha256:benchmark:8e4a417e91c378014ebec9604bce4c41ff631f4521da1d5a52ca5e451118a4a1\", \"capability_id\": \"structured-output\", \"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"planned_cases\": 60, \"profile\": \"core\", \"provider_key\": \"korgis\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_execution_metadata\": {\"artifact_size_bytes\": 4121781472, \"backend\": \"llama_server\", \"quantization\": \"UD-Q2_K_XL\", \"runtime_config\": {\"backend\": \"llama_server\", \"ctx_size\": 8192, \"enable_thinking\": false, \"flash_attn\": true, \"max_kv_size\": null, \"n_batch\": 512, \"n_gpu_layers\": 0, \"n_threads\": 8, \"n_ubatch\": 512, \"offload_kqv\": true, \"show_thinking\": false, \"timeout\": 1200, \"use_mmap\": true}, \"runtime_key\": \"qwen3.5-9b-ud-q2kxl\", \"runtime_source\": \"korgis\"}, \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"started","timestamp_utc":"2026-10-13T11:43:12.376221+00:00"},{"attempt":null,"capability_id":"structured-output","case_id":null,"dataset_id":null,"duration_ms":null,"error_message":null,"error_type":null,"event_id":"07d3a1df-bde4-443d-be57-0b91a0702082","event_type":"capability.completed","metadata_json":"{\"benchmark_signature\": \"sha256:benchmark:8e4a417e91c378014ebec9604bce4c41ff631f4521da1d5a52ca5e451118a4a1\", \"capability_id\": \"structured-output\", \"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"profile\": \"core\", \"provider_key\": \"korgis\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_execution_metadata\": {\"artifact_size_bytes\": 4121781472, \"backend\": \"llama_server\", \"quantization\": \"UD-Q2_K_XL\", \"runtime_config\": {\"backend\": \"llama_server\", \"ctx_size\": 8192, \"enable_thinking\": false, \"flash_attn\": true, \"max_kv_size\": null, \"n_batch\": 512, \"n_gpu_layers\": 0, \"n_threads\": 8, \"n_ubatch\": 512, \"offload_kqv\": true, \"show_thinking\": false, \"timeout\": 1200, \"use_mmap\": true}, \"runtime_key\": \"qwen3.5-9b-ud-q2kxl\", \"runtime_source\": \"korgis\"}, \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"completed","timestamp_utc":"2026-10-13T11:45:53.475798+00:00"},{"attempt":null,"capability_id":null,"case_id":null,"dataset_id":null,"duration_ms":null,"error_message":null,"error_type":null,"event_id":"8d89a2fb-61a2-4e67-b758-b9b374bb4a79","event_type":"model.release.started","metadata_json":"{\"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"provider_key\": \"korgis\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_execution_metadata\": {\"artifact_size_bytes\": 4121781472, \"backend\": \"llama_server\", \"quantization\": \"UD-Q2_K_XL\", \"runtime_config\": {\"backend\": \"llama_server\", \"ctx_size\": 8192, \"enable_thinking\": false, \"flash_attn\": true, \"max_kv_size\": null, \"n_batch\": 512, \"n_gpu_layers\": 0, \"n_threads\": 8, \"n_ubatch\": 512, \"offload_kqv\": true, \"show_thinking\": false, \"timeout\": 1200, \"use_mmap\": true}, \"runtime_key\": \"qwen3.5-9b-ud-q2kxl\", \"runtime_source\": \"korgis\"}, \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"started","timestamp_utc":"2026-10-13T11:45:53.475979+00:00"},{"attempt":null,"capability_id":null,"case_id":null,"dataset_id":null,"duration_ms":401.5975419897586,"error_message":null,"error_type":null,"event_id":"f19eee0a-a24e-44c0-9ec2-49df1990fd5f","event_type":"model.release.completed","metadata_json":"{\"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"provider_key\": \"korgis\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"runtime_execution_metadata\": {\"artifact_size_bytes\": 4121781472, \"backend\": \"llama_server\", \"quantization\": \"UD-Q2_K_XL\", \"runtime_config\": {\"backend\": \"llama_server\", \"ctx_size\": 8192, \"enable_thinking\": false, \"flash_attn\": true, \"max_kv_size\": null, \"n_batch\": 512, \"n_gpu_layers\": 0, \"n_threads\": 8, \"n_ubatch\": 512, \"offload_kqv\": true, \"show_thinking\": false, \"timeout\": 1200, \"use_mmap\": true}, \"runtime_key\": \"qwen3.5-9b-ud-q2kxl\", \"runtime_source\": \"korgis\"}, \"runtime_key\": \"korgis-local\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"completed","timestamp_utc":"2026-10-13T11:45:53.877739+00:00"},{"attempt":null,"capability_id":"structured-output","case_id":null,"dataset_id":null,"duration_ms":null,"error_message":null,"error_type":null,"event_id":"cf70e6e7-a14e-4536-8e26-e87f21444eb2","event_type":"capability.aggregated","metadata_json":"{\"aggregate_count\": 7, \"benchmark_signature\": \"sha256:benchmark:8e4a417e91c378014ebec9604bce4c41ff631f4521da1d5a52ca5e451118a4a1\", \"capability_id\": \"structured-output\", \"execution_signature\": \"sha256:execution:cd1f305d12290c8876ae51ede9cdcf77e484bf49aacbae7597405bab9f818519\", \"model_key\": \"qwen3.5-9b-ud-q2kxl\", \"model_signature\": \"sha256:model:699302e2aa5f01b4eb6102a1011e1a74dc17b41392b003f53ae05cb18e7388c2\", \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\"}","model_key":"qwen3.5-9b-ud-q2kxl","run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":"completed","timestamp_utc":"2026-10-13T11:45:53.885502+00:00"},{"attempt":null,"capability_id":null,"case_id":null,"dataset_id":null,"duration_ms":null,"error_message":null,"error_type":null,"event_id":"8f0d184e-59ad-49a1-a724-1f33086f8eef","event_type":"run.completed","metadata_json":"{\"aggregate_count\": 7, \"completed_cases\": 60, \"failed_cases\": 0, \"model_failures\": 0, \"planned_cases\": 60, \"run_group\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl\", \"run_id\": \"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core\", \"skipped_cases\": 0}","model_key":null,"run_id":"qwen-variants-core-qwen3.5-9b-ud-q2kxl-structured-output-core","sample_id":null,"status":null,"timestamp_utc":"2026-10-13T11:45:53.885678+00:00"}]}},"schema_version":"1"}
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/dashboard_export.py b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/dashboard_export.py
index 79fc0c6c..d6ba6b43 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/dashboard_export.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/dashboard_export.py
@@ -9,6 +9,7 @@
     build_decision_overview,
 )
 from model_capability_bench.analytics.pareto import build_frontier_payload
+from model_capability_bench.analytics.public_bundle import write_public_bundle
 from model_capability_bench.analytics.sensitivity import build_sensitivity_payload
 from model_capability_bench.runner.comparison import paired_binary_comparison
 
@@ -40,7 +41,12 @@ def export_dashboard_data(
     *,
     database_path: Path,
     output_dir: Path,
+    result_view: str = "latest",
+    public_output_path: Path | None = None,
 ) -> dict[str, str]:
+    if result_view not in {"latest", "standard"}:
+        raise ValueError("result_view must be latest or standard")
+    quality_view = "v_latest_quality_results" if result_view == "latest" else "v_current_quality_results"
     database_path = database_path.resolve()
     output_dir = output_dir.resolve()
     output_dir.mkdir(parents=True, exist_ok=True)
@@ -49,7 +55,7 @@ def export_dashboard_data(
     try:
         current = _rows(
             connection,
-            """
+            f"""
             SELECT
                 q.run_id,
                 q.model_key,
@@ -76,13 +82,16 @@ def export_dashboard_data(
                 m.artifact_format,
                 m.family,
                 m.parameters_b,
-                m.artifact_size_bytes
-            FROM v_current_quality_results q
+                m.artifact_size_bytes,
+                rc.experiment_kind,
+                rc.inference_json AS generation_policy
+            FROM {quality_view} q
             JOIN models m
               ON m.run_id = q.run_id
              AND m.model_key = q.model_key
             JOIN runs r
               ON r.run_id = q.run_id
+            LEFT JOIN run_configurations rc ON rc.run_id = q.run_id
             ORDER BY q.capability_id, q.model_key
             """,
         )
@@ -111,6 +120,7 @@ def export_dashboard_data(
             for row in current_resources
         }
         for row in current:
+            row["generation_policy"] = _decode_json(row.get("generation_policy"))
             row["resource_summary"] = resources_by_cell.get(
                 (
                     str(row["run_id"]),
@@ -168,6 +178,12 @@ def export_dashboard_data(
         sensitivity = build_sensitivity_payload(connection)
         overview = {
             "schema_version": "2",
+            "result_view": result_view,
+            "consolidations": [
+                {"run_id": row["run_id"], "model_key": row["model_key"],
+                 "capability_id": row["capability_id"], "generation_policy": row["generation_policy"]}
+                for row in current if row.get("experiment_kind") == "consolidated"
+            ],
             "models": list(models.values()),
             "capabilities": capabilities,
             "cells": current,
@@ -214,7 +230,7 @@ def export_dashboard_data(
                 sig = benchmark_signatures[0]
                 case_rows = _rows(
                     connection,
-                    """
+                    f"""
                     SELECT
                         c.run_id,
                         c.case_id,
@@ -245,7 +261,7 @@ def export_dashboard_data(
                       AND c.benchmark_signature = ?
                       AND c.run_id IN (
                           SELECT run_id
-                          FROM v_current_quality_results
+                          FROM {quality_view}
                           WHERE capability_id = ?
                             AND benchmark_signature = ?
                       )
@@ -589,7 +605,15 @@ def comparison_evidence(
     finally:
         connection.close()
 
+    if public_output_path is None:
+        public_output_path = (
+            output_dir.parent.parent / "published" / "dashboard-data.json"
+            if output_dir.name == "dashboard" and output_dir.parent.name == "analytics"
+            else output_dir / "dashboard-data.json"
+        )
+    bundle_path = write_public_bundle(output_dir, destination=public_output_path)
     return {
         "index": str(output_dir / "index.json"),
         "overview": str(output_dir / "overview.json"),
+        "bundle": str(bundle_path),
     }
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/decision_summary.py b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/decision_summary.py
index 7737e157..d089fb74 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/decision_summary.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/decision_summary.py
@@ -704,8 +704,15 @@ def build_decision_overview(
                 "artifact_format": cell.get("artifact_format") or artifact.get("format"),
                 "artifact_size_bytes": artifact.get("size_bytes"),
                 "tags": cfg.get("tags") or [],
+                "result_policy": (
+                    "consolidated-latest-attempt"
+                    if cell.get("experiment_kind") == "consolidated" else "standard"
+                ),
             }
 
+        if cell.get("experiment_kind") == "consolidated":
+            model_meta[model_key]["result_policy"] = "consolidated-latest-attempt"
+
     capability_count = len(selected_signatures)
     dataset_ids = sorted({str(row["dataset_id"]) for row in cases})
     model_summaries: list[dict[str, Any]] = []
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/projector.py b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/projector.py
index 43b92a12..ddc65b82 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/projector.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/projector.py
@@ -410,6 +410,26 @@ def _create_schema(connection: Any) -> None:
         )
         WHERE rn = 1;
 
+        CREATE OR REPLACE VIEW v_latest_quality_results AS
+        WITH consolidated AS (
+            SELECT b.*,
+                ROW_NUMBER() OVER (
+                    PARTITION BY b.model_signature, b.capability_id, b.profile
+                    ORDER BY b.completed_at_utc DESC, b.run_id DESC
+                ) AS rn
+            FROM benchmark_cells b
+            JOIN run_configurations rc ON rc.run_id = b.run_id
+            WHERE b.status = 'COMPLETED' AND rc.experiment_kind = 'consolidated'
+        )
+        SELECT * EXCLUDE (rn) FROM consolidated WHERE rn = 1
+        UNION ALL
+        SELECT q.* FROM v_current_quality_results q
+        WHERE NOT EXISTS (
+            SELECT 1 FROM consolidated c
+            WHERE c.rn = 1 AND c.model_signature = q.model_signature
+              AND c.capability_id = q.capability_id AND c.profile = q.profile
+        );
+
         CREATE OR REPLACE VIEW v_model_history AS
         SELECT
             b.*,
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/analytics/public_bundle.py b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/public_bundle.py
new file mode 100644
index 00000000..dc6ee1e2
--- /dev/null
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/analytics/public_bundle.py
@@ -0,0 +1,80 @@
+"""Single-file public dashboard data, published with atomic replacement."""
+from __future__ import annotations
+
+import json
+import os
+import re
+import tempfile
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+_PRIVATE_KEYS = {
+    "source_dir", "cwd", "executable", "model_path", "mmproj_path", "artifact_path",
+    "llama_server_bin", "local_path", "home", "hostname", "username", "user_name",
+    "environ", "environment_variables", "api_key", "authorization", "password",
+    "secret", "access_token", "refresh_token", "hf_token", "api_token", "auth_token",
+    "bearer_token", "token",
+}
+_LOCAL_PATH = re.compile(r"(?:/Users/|/home/|/private/|/var/|/tmp/|[A-Za-z]:[\\/])")
+
+
+def public_value(value: Any) -> Any:
+    if isinstance(value, dict):
+        clean = {}
+        for key, item in value.items():
+            name = key.lower()
+            if name in _PRIVATE_KEYS or name.endswith(("_api_key", "_password", "_secret")):
+                clean[key] = None
+            elif name.endswith("_json") and isinstance(item, str):
+                try:
+                    decoded = json.loads(item)
+                except json.JSONDecodeError:
+                    clean[key] = public_value(item)
+                else:
+                    clean[key] = json.dumps(public_value(decoded), sort_keys=True)
+            else:
+                clean[key] = public_value(item)
+        return clean
+    if isinstance(value, list):
+        return [public_value(item) for item in value]
+    if isinstance(value, str) and (
+        _LOCAL_PATH.search(value) or re.search(r"https?://[^/\s]+:[^/\s]+@", value)
+    ):
+        return "[redacted local or credential-bearing value]"
+    return value
+
+
+def write_public_bundle(data_dir: Path, *, destination: Path) -> Path:
+    """Read only files referenced by this export's index, excluding stale files."""
+    index = json.loads((data_dir / "index.json").read_text())
+
+    def read(relative: str) -> Any:
+        path = (data_dir / relative).resolve()
+        if not path.is_relative_to(data_dir.resolve()):
+            raise ValueError("Dashboard index references a file outside its export directory")
+        return json.loads(path.read_text())
+
+    bundle = public_value({
+        "schema_version": "1",
+        "generated_at_utc": datetime.now(UTC).isoformat(),
+        "overview": read(index["overview"]),
+        **{section: {key: read(relative) for key, relative in index[section].items()}
+           for section in ("capabilities", "models", "runs")},
+    })
+    # Serialize first: failures must leave the previously published file intact.
+    content = json.dumps(bundle, ensure_ascii=False, sort_keys=True, separators=(",", ":")) + "\n"
+    destination = destination.resolve()
+    destination.parent.mkdir(parents=True, exist_ok=True)
+    fd, temp_name = tempfile.mkstemp(prefix=f".{destination.name}.", dir=destination.parent)
+    temporary = Path(temp_name)
+    try:
+        with os.fdopen(fd, "w", encoding="utf-8") as handle:
+            handle.write(content)
+            handle.flush()
+            os.fsync(handle.fileno())
+        os.chmod(temporary, 0o644)
+        os.replace(temporary, destination)
+    finally:
+        temporary.unlink(missing_ok=True)
+    return destination
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/cli.py b/experiments/model-capability-benchmark/src/model_capability_bench/cli.py
index f190f8a8..b27eb82b 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/cli.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/cli.py
@@ -34,9 +34,11 @@
     load_sweep,
 )
 from model_capability_bench.runner.config import load_runner_defaults
+from model_capability_bench.runner.consolidation import consolidate_runs
 from model_capability_bench.runner.manifest import write_run_artifacts
 from model_capability_bench.runner.planning import plan_benchmark
 from model_capability_bench.runner.progress import TerminalProgress
+from model_capability_bench.runner.recovery import select_error_cases
 from model_capability_bench.runtimes import RegistryRuntimeResolver
 from model_capability_bench.sharing import create_share_snapshot, render_share_snapshot
 from model_capability_bench.suite import (
@@ -80,6 +82,12 @@ def build_parser() -> argparse.ArgumentParser:
     run.add_argument("--run-id")
     run.add_argument("--output-dir", type=Path)
     run.add_argument("--cache-dir", type=Path)
+    run.add_argument("--max-output-tokens", type=int)
+    run.add_argument(
+        "--rerun-errors-from", type=Path, action="append", default=[],
+        help="Select invalid/failed latest cases from a source run directory; repeat for multiple runs.",
+    )
+    run.add_argument("--plan-only", action="store_true", help="Print selection without inference.")
     run.add_argument(
         "--progress",
         action=argparse.BooleanOptionalAction,
@@ -158,6 +166,15 @@ def build_parser() -> argparse.ArgumentParser:
     project.add_argument("--rebuild", action="store_true")
     project.add_argument("--export-dashboard", action="store_true")
 
+    project.add_argument("--result-view", choices=("latest", "standard"), default="latest")
+
+    consolidate = sub.add_parser("consolidate", help="Create an immutable latest-attempt consolidated run.")
+    consolidate.add_argument("--run-dir", type=Path, action="append", required=True)
+    consolidate.add_argument("--run-id", required=True)
+    consolidate.add_argument("--run-group", required=True)
+    consolidate.add_argument("--output-dir", type=Path)
+    consolidate.add_argument("--plan-only", action="store_true")
+
     dashboard_data = sub.add_parser(
         "dashboard-data",
         help="Export typed dashboard JSON from the analytics database.",
@@ -165,6 +182,7 @@ def build_parser() -> argparse.ArgumentParser:
     dashboard_data.add_argument("--results-root", type=Path)
     dashboard_data.add_argument("--database", type=Path)
     dashboard_data.add_argument("--output-dir", type=Path)
+    dashboard_data.add_argument("--result-view", choices=("latest", "standard"), default="latest")
 
     dashboard_build = sub.add_parser(
         "dashboard-build",
@@ -262,6 +280,19 @@ def main() -> int:
     args = build_parser().parse_args()
     root = args.root.resolve()
 
+    if args.command == "consolidate":
+        output = args.output_dir or root / "results" / "runs" / args.run_id
+        summary = consolidate_runs(
+            sources=args.run_dir, output_dir=output, run_id=args.run_id,
+            run_group=args.run_group, suite=load_capability_suite(root), plan_only=args.plan_only,
+        )
+        if not args.plan_only:
+            reporting_config = load_reporting_config(root)
+            report = load_benchmark_report(output, reporting_config)
+            write_report(report, reporting_config, output)
+        _json(summary)
+        return 0
+
     if args.command == "project":
         results_root = (
             args.results_root.resolve()
@@ -288,6 +319,8 @@ def main() -> int:
             payload["dashboard"] = export_dashboard_data(
                 database_path=database,
                 output_dir=results_root / "analytics" / "dashboard",
+                result_view=args.result_view,
+                public_output_path=results_root / "published" / "dashboard-data.json",
             )
         _json(payload)
         return 0
@@ -312,6 +345,8 @@ def main() -> int:
             export_dashboard_data(
                 database_path=database,
                 output_dir=output_dir,
+                result_view=args.result_view,
+                public_output_path=results_root / "published" / "dashboard-data.json",
             )
         )
         return 0
@@ -615,7 +650,37 @@ def main() -> int:
         if args.cache_dir is not None
         else defaults.cache_dir
     )
-
+    if args.max_output_tokens is not None and args.max_output_tokens < 1:
+        raise ValueError("--max-output-tokens must be positive")
+    inference_config = (
+        {"max_output_tokens": args.max_output_tokens}
+        if args.max_output_tokens is not None else {}
+    )
+    selected_cases = None
+    recovery_metadata = {}
+    if args.rerun_errors_from:
+        if output_dir.resolve() in {path.resolve() for path in args.rerun_errors_from}:
+            raise ValueError("Recovery output must differ from source run directories")
+        selected_cases, recovery_metadata = select_error_cases(
+            args.rerun_errors_from, models=model_keys, capabilities=capability_ids,
+            profile=profile, seed=seed,
+        )
+        if resolved_run_id in {item["run_id"] for item in recovery_metadata["recovery_sources"]}:
+            raise ValueError("Recovery requires a new run ID")
+        existing_manifest = output_dir / "run_manifest.json"
+        if existing_manifest.exists():
+            existing = json.loads(existing_manifest.read_text())
+            previous = existing["run"].get("metadata", {})
+            if (existing["configuration"]["experiment_kind"] != "recovery"
+                or existing["configuration"]["inference"] != inference_config
+                or any(previous.get(key) != value for key, value in recovery_metadata.items())):
+                raise ValueError("Use a new run ID: recovery selection or configuration changed")
+        elif output_dir.exists() and any(output_dir.iterdir()):
+            raise ValueError("Recovery requires an empty output directory or a matching recovery manifest")
+    if args.plan_only:
+        _json({"selected_cases": selected_cases, "selected_case_count": len(selected_cases) if selected_cases else None,
+               "inference": inference_config, "output_dir": str(output_dir), "metadata": recovery_metadata})
+        return 0
     config = RunnerConfig(
         run_group=args.run_group,
         profile=profile,
@@ -625,6 +690,9 @@ def main() -> int:
         resume=resume,
         retry_failures=retry_failures,
         run_id=resolved_run_id,
+        inference_config=inference_config,
+        selected_cases=selected_cases,
+        metadata=recovery_metadata,
     )
     with TerminalProgress(enabled=args.progress) as progress:
         runtime_resolver = RegistryRuntimeResolver(os.environ)
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/providers/openai_json.py b/experiments/model-capability-benchmark/src/model_capability_bench/providers/openai_json.py
index 93ed0a9d..e02b0019 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/providers/openai_json.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/providers/openai_json.py
@@ -17,7 +17,6 @@
 from benchmark_core.transports import create_openai_compatible_client
 from openai import OpenAI
 
-
 from model_capability_bench.providers.parsing import parse_chat_response_content
 
 
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/runner/consolidation.py b/experiments/model-capability-benchmark/src/model_capability_bench/runner/consolidation.py
new file mode 100644
index 00000000..a387b17b
--- /dev/null
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/runner/consolidation.py
@@ -0,0 +1,230 @@
+"""Immutable, latest-attempt consolidation of compatible benchmark evidence."""
+from __future__ import annotations
+
+import copy
+import hashlib
+import json
+import shutil
+import tempfile
+from collections import defaultdict
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+from benchmark_core import read_jsonl_records, sha256_file
+
+from model_capability_bench.runner.aggregation import aggregate_capability
+from model_capability_bench.suite import CapabilitySuiteBundle
+
+
+def _digest(value: Any) -> str:
+    return hashlib.sha256(json.dumps(value, sort_keys=True).encode()).hexdigest()
+
+
+def consolidate_runs(
+    *, sources: list[Path], output_dir: Path, run_id: str, run_group: str,
+    suite: CapabilitySuiteBundle, plan_only: bool = False,
+) -> dict[str, Any]:
+    """Select by logical identity and terminal timestamp; never select by score."""
+    output_dir = output_dir.resolve()
+    if not run_id.strip() or not run_group.strip():
+        raise ValueError("Consolidation needs non-empty run ID and group")
+    if output_dir.exists():
+        raise ValueError("Consolidation output already exists; choose a new run ID")
+    source_paths = sorted({p.resolve() for p in sources})
+    if not source_paths:
+        raise ValueError("Consolidation requires source runs")
+    selected: dict[tuple, dict] = {}
+    provenance = []
+    model_defs: dict[str, dict] = {}
+    cap_defs: dict[str, dict] = {}
+    identities: dict[tuple, tuple] = {}
+    suite_identity = None
+    source_ids: set[str] = set()
+    for path in source_paths:
+        if path == output_dir or path in output_dir.parents:
+            raise ValueError("Consolidation output must be separate from its sources")
+        manifest = json.loads((path / "run_manifest.json").read_text())
+        source_id = manifest["run"]["run_id"]
+        if source_id == run_id or source_id in source_ids:
+            raise ValueError("Source run IDs must be unique and differ from output run ID")
+        source_ids.add(source_id)
+        identity = manifest["suite"]
+        if suite_identity is not None and identity != suite_identity:
+            raise ValueError("Source suite versions, profiles and seeds must match")
+        suite_identity = identity
+        checksums = {name: sha256_file(path / name) for name in (
+            "run_manifest.json", "state.jsonl", "raw.jsonl", "evaluation.jsonl",
+        )}
+        provenance.append({"run_id": source_id, "checksums": checksums})
+        for model in manifest["models"]:
+            key = model["model_key"]
+            if key in model_defs and model_defs[key]["model_signature"] != model["model_signature"]:
+                raise ValueError("Cannot consolidate different artifacts under the same model key")
+            model_defs[key] = model
+        for cap in manifest["capabilities"]:
+            key = cap["capability_id"]
+            if key in cap_defs and any(cap_defs[key].get(k) != cap.get(k) for k in (
+                "task_id", "dataset_ids", "metrics",
+            )):
+                raise ValueError("Source capability definitions must match")
+            cap_defs[key] = cap
+        raw = {(row["case_id"], row["attempt"]): row
+               for row in read_jsonl_records(path / "raw.jsonl")}
+        evaluations = {(row["case_id"], row["attempt"]): row
+                       for row in read_jsonl_records(path / "evaluation.jsonl")}
+        case_identities = {}
+        for state in read_jsonl_records(path / "state.jsonl"):
+            cid = state["case_id"]
+            if "identity" in state:
+                case_identities[cid] = state["identity"]
+            case = case_identities.get(cid)
+            if case is None:
+                raise ValueError("Source state has no case identity")
+            fields = (
+                "model_key", "capability_id", "dataset_id", "dataset_revision",
+                "dataset_split", "sample_id", "task_id", "task_version",
+                "prompt_id", "prompt_version", "suite_id", "suite_version",
+            )
+            if any(not case.get(k) for k in fields):
+                raise ValueError("Source case identity is incomplete")
+            logical = tuple(case[k] for k in fields)
+            semantic_key = (case["model_key"], case["capability_id"], case["dataset_id"])
+            semantic = tuple(case[k] for k in (
+                "dataset_revision", "dataset_split", "task_version", "prompt_id", "prompt_version",
+            ))
+            if semantic_key in identities and identities[semantic_key] != semantic:
+                raise ValueError("Dataset revisions/splits and task/prompt versions must match")
+            identities[semantic_key] = semantic
+            rank = (datetime.fromisoformat(state["timestamp_utc"]), source_id,
+                    int(state["attempt"]), cid)
+            if logical not in selected or rank > selected[logical]["rank"]:
+                selected[logical] = {
+                    "rank": rank, "source_run_id": source_id, "state": state,
+                    "identity": case, "raw": raw.get((cid, state["attempt"])),
+                    "evaluation": evaluations.get((cid, state["attempt"])),
+                }
+        # A source changing while read cannot produce a reproducible snapshot.
+        if any(sha256_file(path / name) != value for name, value in checksums.items()):
+            raise ValueError("Source evidence changed during consolidation; stop the source run first")
+    if not selected:
+        raise ValueError("Source runs contain no cases")
+    evidence = [selected[key] for key in sorted(selected)]
+    for item in evidence:
+        if item["state"]["status"] != "completed" or not item["raw"] or not item["evaluation"]:
+            raise ValueError("Latest attempt is incomplete or lacks paired inference/evaluation evidence; recover it first")
+    current_caps = {cap.spec.capability_id: cap.spec for cap in suite.resolved_capabilities}
+    for key, cap in cap_defs.items():
+        current = current_caps.get(key)
+        if current is None or [
+            {"name": m.name, "source": m.source, "reducer": m.reducer,
+             "field": m.field, "primary": m.primary} for m in current.metrics
+        ] != cap["metrics"]:
+            raise ValueError("Current metric definitions differ from source; cannot recalculate safely")
+    generation = sorted({json.dumps(item["identity"]["generation"], sort_keys=True) for item in evidence})
+    invalid = sum(not item["raw"]["record"]["valid"] or not item["evaluation"]["record"]["valid"]
+                  for item in evidence)
+    summary = {
+        "run_id": run_id, "run_group": run_group, "planned_cases": len(evidence),
+        "completed_cases": len(evidence), "failed_cases": 0, "skipped_cases": 0,
+        "model_failures": 0, "output_dir": str(output_dir),
+        "invalid_cases": invalid, "failure_rate": invalid / len(evidence),
+        "generation_configs": [json.loads(g) for g in generation],
+        "mixed_generation": len(generation) > 1,
+    }
+    if plan_only:
+        return summary
+    now = datetime.now(UTC).isoformat()
+    signatures = {"models": {}, "executions": {}, "benchmarks": {}}
+    for key, model in model_defs.items():
+        signatures["models"][key] = model["model_signature"]
+        executions = sorted({item["raw"]["metadata"]["execution_signature"] for item in evidence
+                             if item["identity"]["model_key"] == key})
+        execution = executions[0] if len(executions) == 1 else "sha256:execution:" + _digest(executions)
+        signatures["executions"][key] = execution
+        model_defs[key] = {**model, "execution_signature": execution, "execution_metadata": {
+            "runtime_source": "consolidated", "source_execution_signatures": executions,
+        }}
+    for cap in cap_defs:
+        cap_cases = [item for item in evidence if item["identity"]["capability_id"] == cap]
+        signatures["benchmarks"][cap] = "sha256:consolidated:" + _digest([
+            {"identity": item["identity"], "source_run_id": item["source_run_id"],
+             "case_id": item["state"]["case_id"], "attempt": item["state"]["attempt"]}
+            for item in cap_cases
+        ])
+    metadata = {"experiment_kind": "consolidated", "selection_policy": "latest-attempt-v1",
+                "sources": provenance, "signatures": signatures,
+                "mixed_generation": summary["mixed_generation"],
+                "generation_configs": summary["generation_configs"]}
+    groups = defaultdict(list)
+    for item in evidence:
+        case = item["identity"]
+        meta = {**item["state"]["metadata"], "run_id": run_id, "run_group": run_group,
+                "benchmark_signature": signatures["benchmarks"][case["capability_id"]],
+                "execution_signature": signatures["executions"][case["model_key"]],
+                "consolidation_source": {
+                    "run_id": item["source_run_id"], "case_id": item["state"]["case_id"],
+                    "attempt": item["state"]["attempt"],
+                    "timestamp_utc": item["state"]["timestamp_utc"],
+                    "generation": case["generation"],
+                    "benchmark_signature": item["state"]["metadata"]["benchmark_signature"],
+                    "execution_signature": item["state"]["metadata"]["execution_signature"],
+                }}
+        for kind in ("raw", "evaluation"):
+            row = copy.deepcopy(item[kind])
+            row["metadata"] = meta
+            row["record"].update({"run_id": run_id})
+            if "run_group" in row["record"]:
+                row["record"]["run_group"] = run_group
+            item[kind] = row
+        item["case_id"] = item["state"]["case_id"]
+        item["attempt"] = item["state"]["attempt"]
+        item["state"] = {**item["state"], "metadata": meta, "identity": case}
+        groups[(case["model_key"], case["capability_id"])].append(item)
+    aggregates = []
+    indices = []
+    for (model, cap), items in groups.items():
+        records = aggregate_capability(current_caps[cap], items, model_key=model,
+                                       run_id=run_id, run_group=run_group,
+                                       profile=suite_identity["profile"])
+        for record in records:
+            record.update({"model_signature": signatures["models"][model],
+                           "execution_signature": signatures["executions"][model],
+                           "benchmark_signature": signatures["benchmarks"][cap]})
+        aggregates.extend(records)
+        indices.append({"run_id": run_id, "run_group": run_group, "model_key": model,
+                        "capability_id": cap, "task_id": current_caps[cap].task_id,
+                        "profile": suite_identity["profile"], "failure_count": 0,
+                        "dataset_ids": list(current_caps[cap].dataset_ids),
+                        "cases": [{"case_id": i["case_id"], "attempt": i["attempt"]} for i in items]})
+    summary.update({"aggregate_count": len(aggregates), "metadata": metadata})
+    manifest = {
+        "schema_version": "1", "created_at_utc": now, "run": summary, "suite": suite_identity,
+        "models": list(model_defs.values()), "capabilities": list(cap_defs.values()),
+        "signatures": signatures, "configuration": {
+            "configuration_id": "consolidated", "experiment_kind": "consolidated",
+            "inference": {"mixed_generation": summary["mixed_generation"],
+                          "generation_configs": summary["generation_configs"]},
+        },
+    }
+    for cap in manifest["capabilities"]:
+        cap["benchmark_signature"] = signatures["benchmarks"][cap["capability_id"]]
+    output_dir.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=".consolidate-", dir=output_dir.parent))
+    try:
+        def write_jsonl(name: str, rows: list) -> None:
+            (staging / name).write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows))
+        for kind in ("state", "raw", "evaluation"):
+            write_jsonl(kind + ".jsonl", [item[kind] for item in evidence])
+        write_jsonl("aggregates.jsonl", aggregates)
+        write_jsonl("report_index.jsonl", indices)
+        write_jsonl("events.jsonl", [{"event": "run_completed", "timestamp_utc": now,
+                                     "metadata": {"run_id": run_id}}])
+        (staging / "run_manifest.json").write_text(json.dumps(manifest, indent=2, sort_keys=True))
+        # No single-machine or single-budget performance claim for a consolidated run.
+        (staging / "environment.json").write_text(json.dumps({"consolidation": metadata}))
+        staging.rename(output_dir)
+    finally:
+        if staging.exists():
+            shutil.rmtree(staging)
+    return summary
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/runner/contracts.py b/experiments/model-capability-benchmark/src/model_capability_bench/runner/contracts.py
index d4a2e3b4..f26f9f99 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/runner/contracts.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/runner/contracts.py
@@ -33,6 +33,7 @@ class RunnerConfig:
     inference_config: Mapping[str, object] = field(default_factory=dict)
     runtime_config: Mapping[str, object] = field(default_factory=dict)
     metadata: Mapping[str, object] = field(default_factory=dict)
+    selected_cases: tuple[tuple[str, str, str, str], ...] | None = None
 
     def __post_init__(self) -> None:
         if not self.run_group.strip():
@@ -49,6 +50,8 @@ def __post_init__(self) -> None:
             raise ValueError("capability_ids must not contain empty values")
         if not self.configuration_id.strip():
             raise ValueError("configuration_id must not be empty")
+        if self.selected_cases is not None and not self.selected_cases:
+            raise ValueError("selected_cases must not be empty")
 
 
 @dataclass(frozen=True)
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/runner/engine.py b/experiments/model-capability-benchmark/src/model_capability_bench/runner/engine.py
index 10d45d49..f0cc7f8c 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/runner/engine.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/runner/engine.py
@@ -122,6 +122,12 @@ def run(self, config: RunnerConfig) -> RunnerSummary:
             model_keys=config.model_keys,
             capability_ids=config.capability_ids,
         )
+        selected_cases = set(config.selected_cases) if config.selected_cases is not None else None
+        if selected_cases is not None:
+            matrix = tuple(arm for arm in matrix if any(
+                key[:3] == (arm.model_key, arm.capability_id, arm.dataset_id)
+                for key in selected_cases
+            ))
         capability_ids = tuple(
             dict.fromkeys(arm.capability_id for arm in matrix)
         )
@@ -331,7 +337,13 @@ def run(self, config: RunnerConfig) -> RunnerSummary:
                         metadata={
                             **capability_metadata,
                             "planned_cases": sum(
-                                len(loaded_for_capability[dataset_id].samples)
+                                sum(
+                                    selected_cases is None or (
+                                        model.model.model_key, capability.spec.capability_id,
+                                        dataset_id, sample.sample_id,
+                                    ) in selected_cases
+                                    for sample in loaded_for_capability[dataset_id].samples
+                                )
                                 for dataset_id in capability.spec.dataset_ids
                             ),
                         },
@@ -340,7 +352,19 @@ def run(self, config: RunnerConfig) -> RunnerSummary:
 
                     for dataset_id in capability.spec.dataset_ids:
                         loaded = loaded_for_capability[dataset_id]
-                        planned_cases += len(loaded.samples)
+                        samples = tuple(sample for sample in loaded.samples if (
+                            selected_cases is None or (
+                                model.model.model_key, capability.spec.capability_id,
+                                dataset_id, sample.sample_id,
+                            ) in selected_cases
+                        ))
+                        if selected_cases is not None:
+                            expected = {key[3] for key in selected_cases if key[:3] == (
+                                model.model.model_key, capability.spec.capability_id, dataset_id,
+                            )}
+                            if expected != {sample.sample_id for sample in samples}:
+                                raise ValueError("Recovery samples no longer match the current dataset selection")
+                        planned_cases += len(samples)
                         task_context = TaskExecutionContext(
                             run_id=identity.run_id,
                             dataset_id=dataset_id,
@@ -349,7 +373,7 @@ def run(self, config: RunnerConfig) -> RunnerSummary:
                             metadata=context_metadata,
                         )
 
-                        for sample in loaded.samples:
+                        for sample in samples:
                             case_identity = BenchmarkCaseIdentity(
                                 suite_id=self.suite.suite.suite_id,
                                 suite_version=self.suite.suite.version,
@@ -602,7 +626,7 @@ def run(self, config: RunnerConfig) -> RunnerSummary:
                             self.evidence_store.complete_case(
                                 case_id,
                                 attempt,
-                                metadata=case_metadata,
+                                metadata={**case_metadata, "valid": bool(task_result.valid)},
                             )
                             completed_cases += 1
                     self.evidence_store.record_stage_event(
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/runner/recovery.py b/experiments/model-capability-benchmark/src/model_capability_bench/runner/recovery.py
new file mode 100644
index 00000000..48a573f2
--- /dev/null
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/runner/recovery.py
@@ -0,0 +1,50 @@
+"""Select unsuccessful latest logical cases without rewriting source evidence."""
+from __future__ import annotations
+
+import hashlib
+import json
+from pathlib import Path
+
+CaseSelection = tuple[str, str, str, str]
+
+
+def select_error_cases(
+    sources: list[Path], *, models: tuple[str, ...], capabilities: tuple[str, ...],
+    profile: str, seed: int,
+) -> tuple[tuple[CaseSelection, ...], dict[str, object]]:
+    latest: dict[CaseSelection, dict] = {}
+    provenance = []
+    for source in sorted({path.resolve() for path in sources}):
+        manifest = json.loads((source / "run_manifest.json").read_text())
+        suite = manifest["suite"]
+        if suite["profile"] != profile or suite["seed"] != seed:
+            raise ValueError("Recovery must use the source profile and seed")
+        state_bytes = (source / "state.jsonl").read_bytes()
+        provenance.append({
+            "run_id": manifest["run"]["run_id"],
+            "state_sha256": hashlib.sha256(state_bytes).hexdigest(),
+        })
+        for line in state_bytes.decode().splitlines():
+            row = json.loads(line)
+            meta = row["metadata"]
+            key = tuple(str(meta.get(k) or "") for k in (
+                "model_key", "capability_id", "dataset_id", "sample_id",
+            ))
+            if key[0] not in models or key[1] not in capabilities:
+                continue
+            if not all(key):
+                raise ValueError("Source case is missing recovery identity fields")
+            previous = latest.get(key)
+            if previous is None or row["timestamp_utc"] > previous["timestamp_utc"]:
+                latest[key] = row
+    selected = tuple(sorted(key for key, row in latest.items() if (
+        row["status"] == "failed"
+        or (row["status"] == "completed" and row["metadata"].get("valid") is False)
+    )))
+    if not selected:
+        raise ValueError("No unsuccessful cases match the selected models/capabilities")
+    return selected, {
+        "experiment_kind": "recovery",
+        "recovery_sources": provenance,
+        "recovery_cases": [list(key) for key in selected],
+    }
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/runtimes/external.py b/experiments/model-capability-benchmark/src/model_capability_bench/runtimes/external.py
index 005e4eb3..9aae28c2 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/runtimes/external.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/runtimes/external.py
@@ -29,4 +29,3 @@ def release(self, model: ResolvedModel) -> None:
             closer = getattr(provider, "close", None) or getattr(provider, "release", None)
             if callable(closer):
                 closer()
-        return None
diff --git a/experiments/model-capability-benchmark/src/model_capability_bench/suite.py b/experiments/model-capability-benchmark/src/model_capability_bench/suite.py
index cfe36ee8..621c7b66 100644
--- a/experiments/model-capability-benchmark/src/model_capability_bench/suite.py
+++ b/experiments/model-capability-benchmark/src/model_capability_bench/suite.py
@@ -20,7 +20,6 @@
 from model_capability_bench.datasets import build_dataset_registry
 from model_capability_bench.tasks import build_task_registry
 
-
 CAPABILITY_ALIASES: Mapping[str, str] = {
     "mathematics": "mathematical-reasoning",
     "math": "mathematical-reasoning",
diff --git a/experiments/model-capability-benchmark/suite.yaml b/experiments/model-capability-benchmark/suite.yaml
index b7201a6a..50642af5 100644
--- a/experiments/model-capability-benchmark/suite.yaml
+++ b/experiments/model-capability-benchmark/suite.yaml
@@ -8,7 +8,7 @@ suite:
 
   generation:
     temperature: 0.0
-    max_output_tokens: 256
+    max_output_tokens: 2048
     seed: 42
 
   capabilities:
diff --git a/experiments/model-capability-benchmark/tests/test_consolidation.py b/experiments/model-capability-benchmark/tests/test_consolidation.py
new file mode 100644
index 00000000..43fdd824
--- /dev/null
+++ b/experiments/model-capability-benchmark/tests/test_consolidation.py
@@ -0,0 +1,160 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import duckdb
+import pytest
+from benchmark_core import read_jsonl_records, sha256_file
+
+from model_capability_bench.analytics.dashboard_export import export_dashboard_data
+from model_capability_bench.analytics.projector import project_results
+from model_capability_bench.runner.consolidation import consolidate_runs
+from model_capability_bench.suite import load_capability_suite
+
+ROOT = Path(__file__).resolve().parents[1]
+MODEL = "lfm2.5-24b-a2b-ud-q3-k-xl"
+CAP = "mathematical-reasoning"
+
+
+def _source(base: Path, name: str, samples: list[tuple[str, bool]], *, tokens: int, day: int) -> Path:
+    from benchmark_core import to_jsonable
+
+    cap = next(c.spec for c in load_capability_suite(ROOT).resolved_capabilities if c.spec.capability_id == CAP)
+    path = base / "runs" / name
+    path.mkdir(parents=True)
+    stamp = f"2026-10-{day:02d}T10:00:00+00:00"
+    manifest = {
+        "suite": {"suite_id": "capability-core", "version": "3", "profile": "core", "seed": 42},
+        "run": {"run_id": name, "run_group": "test", "planned_cases": len(samples),
+                "completed_cases": len(samples), "failed_cases": 0, "metadata": {"signatures": {
+                    "models": {MODEL: "model-signature"}, "executions": {MODEL: "execution-signature"},
+                    "benchmarks": {CAP: f"benchmark-{tokens}"},
+                }}},
+        "created_at_utc": stamp,
+        "models": [{"model_key": MODEL, "model_id": "vendor/model", "model_signature": "model-signature",
+                    "execution_signature": "execution-signature", "deployment": "local"}],
+        "capabilities": [{"capability_id": CAP, "task_id": cap.task_id, "dataset_ids": list(cap.dataset_ids),
+                          "metrics": [{k: v for k, v in to_jsonable(m).items() if k != "options"}
+                                      for m in cap.metrics]}],
+    }
+    states, raw, evaluations = [], [], []
+    for sample, valid in samples:
+        cid = f"case-{sample}-{tokens}"
+        meta = {"model_key": MODEL, "capability_id": CAP, "dataset_id": "math-reasoning-controlled-v3",
+                "dataset_revision": "v3", "dataset_split": "controlled", "sample_id": sample,
+                "model_signature": "model-signature", "execution_signature": "execution-signature",
+                "benchmark_signature": f"benchmark-{tokens}", "run_id": name,
+                "run_group": "test", "valid": valid}
+        identity = {**meta, "task_id": CAP, "task_version": "1", "prompt_id": "math", "prompt_version": "1",
+                    "suite_id": "capability-core", "suite_version": "3", "generation": {"max_output_tokens": tokens}}
+        state = {"case_id": cid, "attempt": 1, "timestamp_utc": stamp,
+                 "status": "completed", "metadata": meta, "identity": identity}
+        states.append(state)
+        record = {"run_id": name, "sample_id": sample, "valid": valid, "model_id": "vendor/model",
+                  "task_id": CAP, "input_tokens": 10, "output_tokens": tokens, "latency_ms": 100,
+                  "normalized_output": {"answer": "1"}, "raw_output": {"answer": "1"}}
+        raw.append({**state, "record": record})
+        evaluations.append({**state, "record": {
+            "run_id": name, "sample_id": sample, "task_id": CAP, "valid": valid,
+            "expected": "1", "prediction": "1" if valid else None,
+            "metrics": [{"name": "final_answer_accuracy", "value": int(valid), "primary": True}],
+        }})
+    (path / "run_manifest.json").write_text(json.dumps(manifest))
+    for filename, rows in (("state.jsonl", states), ("raw.jsonl", raw), ("evaluation.jsonl", evaluations)):
+        (path / filename).write_text("".join(json.dumps(row) + "\n" for row in rows))
+    return path
+
+
+def test_latest_attempt_merge_recalculates_metrics_and_preserves_sources(tmp_path: Path) -> None:
+    base = _source(tmp_path, "base", [("a", False), ("b", True), ("c", True)], tokens=2048, day=21)
+    retry = _source(tmp_path, "retry", [("a", True), ("b", False)], tokens=4096, day=22)
+    sources = [base, retry]
+    hashes = {p: sha256_file(p) for source in sources for p in source.iterdir()}
+    output = tmp_path / "runs" / "merged"
+    args = {"sources": sources, "output_dir": output, "run_id": "merged", "run_group": "test",
+            "suite": load_capability_suite(ROOT)}
+    preview = consolidate_runs(**args, plan_only=True)
+    assert not output.exists()
+    assert preview["planned_cases"] == 3
+    assert preview["invalid_cases"] == 1
+    summary = consolidate_runs(**args)
+    assert summary["mixed_generation"] is True
+    assert summary["failure_rate"] == pytest.approx(1 / 3)
+    raw = read_jsonl_records(output / "raw.jsonl")
+    evaluation = read_jsonl_records(output / "evaluation.jsonl")
+    assert len(raw) == len(evaluation) == 3
+    assert {r["record"]["sample_id"]: r["record"]["valid"] for r in raw} == {
+        "a": True, "b": False, "c": True,
+    }
+    assert all(r["metadata"]["consolidation_source"]["run_id"] == "retry" for r in raw
+               if r["record"]["sample_id"] in {"a", "b"})
+    primary = next(r for r in read_jsonl_records(output / "aggregates.jsonl") if r["primary"])
+    assert primary["value"] == pytest.approx(2 / 3)
+    assert primary["sample_count"] == 3
+    assert all(sha256_file(p) == digest for p, digest in hashes.items())
+    # Source ordering has no effect on selected attempts or signatures.
+    other = tmp_path / "runs" / "other"
+    consolidate_runs(**{**args, "sources": list(reversed(sources)), "output_dir": other, "run_id": "other"})
+    assert json.loads((other / "run_manifest.json").read_text())["signatures"] == json.loads(
+        (output / "run_manifest.json").read_text())["signatures"]
+    with pytest.raises(ValueError, match="already exists"):
+        consolidate_runs(**args)
+
+
+def test_consolidated_projection_updates_latest_but_keeps_canonical_separate(tmp_path: Path) -> None:
+    source = _source(tmp_path, "source", [("a", True), ("b", False)], tokens=2048, day=21)
+    output = tmp_path / "runs" / "merged"
+    consolidate_runs(sources=[source], output_dir=output, run_id="merged", run_group="test",
+                     suite=load_capability_suite(ROOT))
+    projected = project_results(results_root=tmp_path, rebuild=True, run_dirs=(output,))
+    assert projected.projected_runs == 1
+    with duckdb.connect(projected.database_path, read_only=True) as db:
+        assert db.execute("SELECT COUNT(*) FROM v_current_quality_results").fetchone()[0] == 0
+        assert db.execute("SELECT run_id FROM v_latest_quality_results").fetchall() == [("merged",)]
+    exported = export_dashboard_data(database_path=Path(projected.database_path), output_dir=tmp_path / "dashboard")
+    overview = json.loads(Path(exported["overview"]).read_text())
+    public = json.loads(Path(exported["bundle"]).read_text())
+    assert public["overview"]["decision"]["model_summaries"] == overview["decision"]["model_summaries"]
+    assert public["runs"]["merged"]["run"]["source_dir"] is None
+    model = overview["decision"]["model_summaries"][0]
+    assert model["observed_case_count"] == 2
+    assert model["failure_rate"] == 0.5
+    assert model["result_policy"] == "consolidated-latest-attempt"
+    assert overview["consolidations"][0]["run_id"] == "merged"
+    export_dashboard_data(database_path=Path(projected.database_path), output_dir=tmp_path / "standard", result_view="standard")
+    assert json.loads((tmp_path / "standard" / "overview.json").read_text())["cells"] == []
+
+
+def test_incomplete_latest_attempt_cannot_fall_back_to_success(tmp_path: Path) -> None:
+    source = _source(tmp_path, "source", [("a", True)], tokens=2048, day=21)
+    row = json.loads((source / "state.jsonl").read_text())
+    row.update({"status": "failed", "timestamp_utc": "2026-10-22T10:00:00+00:00", "attempt": 2})
+    with (source / "state.jsonl").open("a") as handle:
+        handle.write(json.dumps(row) + "\n")
+    with pytest.raises(ValueError, match="incomplete or lacks paired"):
+        consolidate_runs(sources=[source], output_dir=tmp_path / "merged", run_id="merged",
+                         run_group="test", suite=load_capability_suite(ROOT))
+
+
+@pytest.mark.parametrize("change", ["profile", "artifact", "revision"])
+def test_incompatible_sources_are_rejected_before_writing(tmp_path: Path, change: str) -> None:
+    first = _source(tmp_path, "first", [("a", True)], tokens=2048, day=21)
+    second = _source(tmp_path, "second", [("a", False)], tokens=4096, day=22)
+    manifest_file = second / "run_manifest.json"
+    manifest = json.loads(manifest_file.read_text())
+    if change == "profile":
+        manifest["suite"]["profile"] = "smoke"
+    elif change == "artifact":
+        manifest["models"][0]["model_signature"] = "different-artifact"
+    else:
+        state_file = second / "state.jsonl"
+        row = json.loads(state_file.read_text())
+        row["identity"]["dataset_revision"] = "v4"
+        state_file.write_text(json.dumps(row) + "\n")
+    manifest_file.write_text(json.dumps(manifest))
+    output = tmp_path / "merged"
+    with pytest.raises(ValueError):
+        consolidate_runs(sources=[first, second], output_dir=output, run_id="merged",
+                         run_group="test", suite=load_capability_suite(ROOT))
+    assert not output.exists()
diff --git a/experiments/model-capability-benchmark/tests/test_limite_violetto.py b/experiments/model-capability-benchmark/tests/test_limite_violetto.py
index bfb28dfe..b598df81 100644
--- a/experiments/model-capability-benchmark/tests/test_limite_violetto.py
+++ b/experiments/model-capability-benchmark/tests/test_limite_violetto.py
@@ -3,7 +3,6 @@
 from pathlib import Path
 from types import SimpleNamespace
 
-import pytest
 from benchmark_core import (
     GenerationConfig,
     InferenceRequest,
@@ -18,7 +17,7 @@
     extract_last_boxed_answer,
     parse_chat_response_content,
 )
-from model_capability_bench.suite import CAPABILITY_ALIASES, resolve_capability_id
+from model_capability_bench.suite import resolve_capability_id
 
 ROOT = Path(__file__).resolve().parents[1]
 REGISTRY = ROOT / "models.yaml"
diff --git a/experiments/model-capability-benchmark/tests/test_projector.py b/experiments/model-capability-benchmark/tests/test_projector.py
index c70f25e6..5389dea4 100644
--- a/experiments/model-capability-benchmark/tests/test_projector.py
+++ b/experiments/model-capability-benchmark/tests/test_projector.py
@@ -262,6 +262,25 @@ def _write_run(
     return run_dir
 
 
+def test_recovery_cannot_replace_canonical_current_results(tmp_path: Path) -> None:
+    results = tmp_path / "results"
+    _write_run(results, run_id="canonical", completed_at="2026-10-05T08:00:00+00:00", score=0.7)
+    recovery = _write_run(
+        results, run_id="recovery", completed_at="2026-10-05T09:00:00+00:00", score=1.0,
+    )
+    manifest_path = recovery / "run_manifest.json"
+    manifest = json.loads(manifest_path.read_text())
+    manifest["configuration"] = {"experiment_kind": "recovery"}
+    manifest_path.write_text(json.dumps(manifest))
+    summary = project_results(results_root=results, rebuild=True)
+    with duckdb.connect(summary.database_path, read_only=True) as connection:
+        for view in ("v_current_quality_results", "v_current_performance_results"):
+            assert connection.execute(f"SELECT run_id FROM {view}").fetchall() == [("canonical",)]
+        assert connection.execute("SELECT run_id FROM benchmark_cells ORDER BY run_id").fetchall() == [
+            ("canonical",), ("recovery",),
+        ]
+
+
 def test_projector_selects_latest_completed_comparable_result(tmp_path: Path) -> None:
     results = tmp_path / "results"
     _write_run(
diff --git a/experiments/model-capability-benchmark/tests/test_public_bundle.py b/experiments/model-capability-benchmark/tests/test_public_bundle.py
new file mode 100644
index 00000000..e5d5af18
--- /dev/null
+++ b/experiments/model-capability-benchmark/tests/test_public_bundle.py
@@ -0,0 +1,73 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import pytest
+
+from model_capability_bench.analytics.public_bundle import public_value, write_public_bundle
+
+
+def _export(root: Path) -> None:
+    root.mkdir()
+    index = {"overview": "overview.json", "capabilities": {"cap": "cap.json"},
+             "models": {"model": "model.json"}, "runs": {"run": "run.json"}}
+    (root / "index.json").write_text(json.dumps(index))
+    for name in ("overview", "cap", "model", "run"):
+        (root / f"{name}.json").write_text(json.dumps({"name": name, "failure_rate": 0.03}))
+    (root / "stale.json").write_text(json.dumps({"stale": True}))
+
+
+def test_public_bundle_contains_all_views_and_replaces_previous_snapshot(tmp_path: Path) -> None:
+    root = tmp_path / "export"
+    _export(root)
+    destination = tmp_path / "published" / "dashboard-data.json"
+    write_public_bundle(root, destination=destination)
+    data = json.loads(destination.read_text())
+    assert data["schema_version"] == "1"
+    assert data["overview"]["name"] == "overview"
+    assert data["capabilities"]["cap"]["name"] == "cap"
+    assert data["models"]["model"]["name"] == "model"
+    assert data["runs"]["run"]["name"] == "run"
+    assert "stale" not in destination.read_text()
+    (root / "overview.json").write_text(json.dumps({"failure_rate": 0.01}))
+    write_public_bundle(root, destination=destination)
+    assert json.loads(destination.read_text())["overview"]["failure_rate"] == 0.01
+    assert not list(destination.parent.glob(".dashboard-data.json.*"))
+
+
+def test_failed_export_keeps_public_snapshot_intact(tmp_path: Path) -> None:
+    root = tmp_path / "export"
+    _export(root)
+    destination = tmp_path / "dashboard-data.json"
+    write_public_bundle(root, destination=destination)
+    before = destination.read_bytes()
+    (root / "cap.json").write_text("invalid JSON")
+    with pytest.raises(json.JSONDecodeError):
+        write_public_bundle(root, destination=destination)
+    assert destination.read_bytes() == before
+
+
+def test_public_redaction_handles_serialized_metadata_and_keeps_metrics() -> None:
+    data = public_value({
+        "source_dir": "/Users/private/runs", "failure_rate": 0.03, "output_tokens": 4096,
+        "execution_environment": {"cpu_model": "Apple M3 Pro", "total_memory_bytes": 100},
+        "metadata_json": json.dumps({"model_path": "/Users/private/model.gguf", "api_key": "secret-value", "ctx_size": 8192}),
+        "error_message": "failure at /private/tmp/model.log", "url": "https://user:password@example.com",
+    })
+    encoded = json.dumps(data)
+    assert "/Users/" not in encoded and "/private/" not in encoded
+    assert "secret-value" not in encoded and "user:password" not in encoded
+    assert data["failure_rate"] == 0.03 and data["output_tokens"] == 4096
+    assert data["execution_environment"]["cpu_model"] == "Apple M3 Pro"
+    assert json.loads(data["metadata_json"])["ctx_size"] == 8192
+
+
+def test_bundle_rejects_index_path_traversal(tmp_path: Path) -> None:
+    root = tmp_path / "export"
+    _export(root)
+    index = json.loads((root / "index.json").read_text())
+    index["overview"] = "../outside.json"
+    (root / "index.json").write_text(json.dumps(index))
+    with pytest.raises(ValueError, match="outside"):
+        write_public_bundle(root, destination=tmp_path / "public.json")
diff --git a/experiments/model-capability-benchmark/tests/test_recovery.py b/experiments/model-capability-benchmark/tests/test_recovery.py
new file mode 100644
index 00000000..1f7c4f8e
--- /dev/null
+++ b/experiments/model-capability-benchmark/tests/test_recovery.py
@@ -0,0 +1,77 @@
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+import pytest
+
+from model_capability_bench.runner.recovery import select_error_cases
+
+
+def _source(root: Path, rows: list[dict]) -> Path:
+    root.mkdir()
+    (root / "run_manifest.json").write_text(json.dumps({
+        "suite": {"profile": "core", "seed": 42}, "run": {"run_id": root.name},
+    }))
+    (root / "state.jsonl").write_text("\n".join(json.dumps(row) for row in rows))
+    return root
+
+
+def _row(sample: str, status: str, valid: bool, time: str = "1") -> dict:
+    return {"status": status, "timestamp_utc": time, "metadata": {
+        "model_key": "model", "capability_id": "cap", "dataset_id": "dataset",
+        "sample_id": sample, "valid": valid,
+    }}
+
+
+def test_latest_logical_attempt_controls_recovery_across_sources(tmp_path: Path) -> None:
+    first = _source(tmp_path / "first", [
+        _row("invalid", "completed", False),
+        _row("failed", "failed", False),
+        _row("fixed", "completed", False),
+        _row("valid", "completed", True),
+        _row("interrupted", "started", False),
+    ])
+    second = _source(tmp_path / "second", [_row("fixed", "completed", True, "2")])
+    before = (first / "state.jsonl").read_bytes()
+    selected, metadata = select_error_cases(
+        [second, first], models=("model",), capabilities=("cap",), profile="core", seed=42,
+    )
+    assert {key[3] for key in selected} == {"invalid", "failed"}
+    assert metadata["experiment_kind"] == "recovery"
+    assert len(metadata["recovery_sources"]) == 2
+    assert (first / "state.jsonl").read_bytes() == before
+
+
+def test_recovery_rejects_different_profile_or_empty_selection(tmp_path: Path) -> None:
+    source = _source(tmp_path / "source", [_row("valid", "completed", True)])
+    with pytest.raises(ValueError, match="profile and seed"):
+        select_error_cases([source], models=("model",), capabilities=("cap",), profile="smoke", seed=42)
+    with pytest.raises(ValueError, match="No unsuccessful cases"):
+        select_error_cases([source], models=("model",), capabilities=("cap",), profile="core", seed=42)
+
+
+def test_cli_recovery_preview_and_source_protection(tmp_path: Path, monkeypatch, capsys) -> None:
+    from model_capability_bench.cli import main
+
+    row = _row("bad", "completed", False)
+    row["metadata"]["model_key"] = "lfm2.5-24b-a2b-ud-q3-k-xl"
+    row["metadata"]["capability_id"] = "structured-output"
+    source = _source(tmp_path / "source", [row])
+    output = tmp_path / "output"
+    args = [
+        "model-bench", "run", "--models", row["metadata"]["model_key"],
+        "--capabilities", "structured-output", "--profile", "core",
+        "--run-group", "recovery", "--run-id", "recovery", "--output-dir", str(output),
+        "--max-output-tokens", "4096", "--rerun-errors-from", str(source), "--plan-only",
+    ]
+    monkeypatch.setattr(sys, "argv", args)
+    assert main() == 0
+    payload = json.loads(capsys.readouterr().out)
+    assert payload["selected_case_count"] == 1
+    assert payload["inference"]["max_output_tokens"] == 4096
+    assert not output.exists()
+    args[args.index(str(output))] = str(source)
+    with pytest.raises(ValueError, match="must differ"):
+        main()
diff --git a/experiments/model-capability-benchmark/tests/test_unified_runner.py b/experiments/model-capability-benchmark/tests/test_unified_runner.py
index 76fb3770..2ea239cc 100644
--- a/experiments/model-capability-benchmark/tests/test_unified_runner.py
+++ b/experiments/model-capability-benchmark/tests/test_unified_runner.py
@@ -20,6 +20,51 @@
 ROOT = Path(__file__).resolve().parents[1]
 
 
+def test_recovery_executes_only_selected_samples_with_larger_budget(tmp_path: Path) -> None:
+    import json
+
+    from model_capability_bench.runner.recovery import select_error_cases
+
+    original_root = tmp_path / "original"
+    first = _runner(original_root, runtime=_FakeRuntime())
+    config = RunnerConfig(
+        run_group="original", profile="smoke", model_keys=("qwen3.5-2b-q4km",),
+        capability_ids=("mathematical-reasoning",),
+    )
+    first.run(config)
+    source = original_root / "evidence"
+    states = read_jsonl_records(source / "state.jsonl")
+    completed = [row for row in states if row["status"] == "completed"]
+    chosen = completed[0]["metadata"]["sample_id"]
+    for row in states:
+        if row["status"] == "completed" and row["metadata"]["sample_id"] == chosen:
+            row["metadata"]["valid"] = False
+    (source / "state.jsonl").write_text("\n".join(json.dumps(row) for row in states))
+    (source / "run_manifest.json").write_text(json.dumps({
+        "suite": {"profile": "smoke", "seed": 42}, "run": {"run_id": "original"},
+    }))
+    selected, metadata = select_error_cases(
+        [source], models=config.model_keys, capabilities=config.capability_ids,
+        profile="smoke", seed=42,
+    )
+    before = (source / "state.jsonl").read_bytes()
+    recovery = _runner(tmp_path / "recovery", runtime=_FakeRuntime())
+    retry_config = dataclasses.replace(
+        config, run_group="recovery", selected_cases=selected, metadata=metadata,
+        inference_config={"max_output_tokens": 4096},
+    )
+    summary = recovery.run(retry_config)
+    assert summary.planned_cases == summary.completed_cases == 1
+    raw = read_jsonl_records(tmp_path / "recovery" / "evidence" / "raw.jsonl")
+    assert [row["record"]["sample_id"] for row in raw] == [chosen]
+    started = read_jsonl_records(tmp_path / "recovery" / "evidence" / "state.jsonl")[0]
+    assert started["identity"]["generation"]["max_output_tokens"] == 4096
+    assert (source / "state.jsonl").read_bytes() == before
+    resumed = recovery.run(retry_config)
+    assert resumed.completed_cases == 0
+    assert resumed.skipped_cases == 1
+
+
 class _FakeProvider:
     provider_id = "fake"
 
diff --git a/korgis b/korgis
index 3047842f..5d98b6e9 160000
--- a/korgis
+++ b/korgis
@@ -1 +1 @@
-Subproject commit 3047842f5c0ccba04d673588ea3b78db7ab7a7b4
+Subproject commit 5d98b6e951dfaba4a2a2583574b541cb8f09244c