quantum guard vs averaged rhr, glassbox narrative direction

[abdulsaheel]

dispersionBelowQuantum treated nightly rhr as whole bpm, but nocturnalRhr gives a 30-min mean so it's continuous. a tight real baseline (sd under 1 bpm) got rhr refused from readiness on the night it rose, same for illness/anomaly/event/overreaching. guard now only fires when the baseline actually sits on the quantum grid, integer baselines behave as before.

glassbox narrative took up/down from the oriented contribution so a lower rhr read as "up". uses the raw delta now, and the low band says "a low-readiness day" instead of telling people to take it easy.

edge needs an algo bump when it repins this.

Summary by Sourcery

Refine readiness dispersion guards and glassbox narratives to correctly handle continuous averaged metrics and report driver direction accurately.

Bug Fixes:

• Preserve readiness inputs from tight, genuinely continuous averaged baselines while retaining quantum-dispersion protection for mostly quantized histories.
• Correct readiness narratives to describe metric movement using raw deltas, including lower-is-better metrics such as resting heart rate.
• Use non-prescriptive wording for the low-readiness narrative band.

Enhancements:

• Add coverage for continuous and mixed baseline dispersion behavior and raw-direction narrative generation.

Tests:

• Add regression tests covering averaged RHR baselines, mixed quantized histories, and readiness narrative direction and wording.

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📥 Commits

Reviewing files that changed from the base of the PR and between f548542 and ffb7805.

📒 Files selected for processing (4)

• lib/src/onehz/foundations/baseline.dart
• lib/src/onehz/human/readiness_glassbox.dart
• test/dispersion_guard_test.dart
• test/onehz/human_test.dart

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Reviewer's Guide

The PR differentiates continuous averaged physiological baselines from quantized whole-unit data before applying the dispersion refusal guard, preventing valid RHR inputs from being excluded, and corrects glassbox narratives to report raw metric direction with less prescriptive low-readiness language.

Sequence diagram for raw-direction glassbox readiness narrative

sequenceDiagram
    participant Inputs
    participant Readiness as glassBoxReadiness
    participant Narrative as _buildNarrative
    Inputs->>Readiness: collect metric delta
    Readiness->>Readiness: create _RawItem with delta
    Readiness->>Readiness: rank drivers by contribution
    Readiness->>Narrative: _buildNarrative(score, drivers, topDelta)
    Narrative->>Narrative: choose direction from topDelta
    Narrative-->>Readiness: readiness narrative

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Flow diagram for the quantum dispersion guard

flowchart TD
    A[Baseline values] --> B{All values sit on quantum grid?}
    B -->|No| C[Accept continuous baseline dispersion]
    B -->|Yes| D[Compute standard deviation]
    D --> E{SD below quantum?}
    E -->|Yes| F[Refuse baseline for readiness]
    E -->|No| G[Accept baseline]
    C --> H[Use physiological input in readiness]
    G --> H

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File-Level Changes

Change	Details	Files
Restrict the low-dispersion refusal guard to genuinely quantized baselines.	Detect any baseline value that is off the quantum grid and bypass the quantization guard. Preserve existing refusal behavior for integer/grid-aligned baselines. Add coverage for continuous averaged RHR baselines and ensure RHR remains usable in readiness scoring.	lib/src/onehz/foundations/baseline.dart test/dispersion_guard_test.dart
Make readiness narratives describe raw metric movement and use non-prescriptive low-readiness wording.	Carry each input's raw delta through driver selection. Use the highest-ranked significant driver's raw delta for up/down wording instead of oriented contribution. Rename the low score band to “A low-readiness day” and verify lower-is-better RHR direction and wording.	lib/src/onehz/human/readiness_glassbox.dart test/onehz/human_test.dart

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