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Daily check-in model

The system supports four check-in tiers so users are never blocked from their tasks on low-capacity days.
Three ratings, one per axis using 1-5 circles.
AxisLow anchorHigh anchorMeasures
Body”Moving gently""Feeling strong”Physical capacity
Mind”Foggy today""Sharp and clear”Cognitive capacity
Mood”A hard one""Really good”Emotional state

Data quality across tiers

TierConfidence weightEWMA influencePool accuracy
Full1.0FullBest
Quick0.7ReducedGood
Momentum0.4MinimalApproximate
None0.1NegligibleConservative estimate
Ratings are relative to personal baseline. A 3 means “about my usual,” not an objective severity level.

The onboarding sequence

1

Condition selection

Broad chronic illness categories, not diagnosis-level claims.
2

Severity self-assessment

Initializes the coefficient starting range.
3

Optional Visible import

Optional pace-point import for calibration support.
4

Difficulty calibration

User rates 6 common tasks (1-5), producing initial coefficient estimate.
5

Reference day anchors

User marks what they completed yesterday to seed initial pool estimate.
6

LLM estimation opt-in

Explains on-device vs cloud estimation; default is off.

Cold start pool and confidence

For the first week, pool blends reference estimate with observed behavior:
Day 1:    pool = referenceEstimate x bias
Day 2-7:  pool = blend(referenceEstimate, realSpendingEwma, blendWeight)
Day 8+:   pool = realSpendingEwma x bias
DayConfidenceBiasPool protection
10.000.8020% below reference
10~0.30~0.8515% below spending
27~0.80~0.946% below spending
34~1.000.973% permanent margin
The blend weight increases linearly from day 2 to day 7, avoiding both overconfidence and week-long lock-in to a bad initial guess.