Aptet Fitness
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"interpretation": {
"scoreMeaning": "The effective fit score after applying the conservative confidence penalty. Lower confidence reduces the effective fit score but does not, by itself, imply evidence of poor fit.",
"fitScopeMeaning": "Aptet fit is currently universe-conditioned: activation history and fit depend on the other members in the tested cross-sectional universe.",
"rawScoreMeaning": "The unadjusted Aptet-family fit estimate before applying the conservative confidence penalty.",
"activationMeaning": "Activation count measures how often the Aptet ranking would have selected the stock while risk-on.",
"confidenceMeaning": "Reflects the amount and breadth of historical evidence supporting the family-fit score.",
"algorithmFitMeaning": "Measures how consistently this stock works across the Aptet strategy family within this tested universe, not only under its single best parameter combination.",
"comboQualityMeaning": "Fixed-scale normalized profile quality derived from fitnessScore using sigmoid((fitnessScore - 0.35) / 0.22).",
"fitnessScoreMeaning": "Per-profile raw score used for diagnostics and ranking. Higher is better, but it is not the stock's overall Aptet-family fit.",
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"parameterStabilityMeaning": "Measures whether nearby Aptet parameter combinations retain a large share of the best profile's normalized quality.",
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"strategyOptions": {
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}Force Fitness
{
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"backendMeaning": "This Force evaluator uses the alpha1 backend logic that powers the current Force preview path.",
"fitScopeMeaning": "Force fit is currently universe-conditioned because the stock competes against the tested Force universe at each ranking step.",
"rawScoreMeaning": "The unadjusted Force-family fit estimate before the conservative confidence penalty.",
"algorithmFitMeaning": "Measures how consistently this stock works across the Force strategy family within this tested universe.",
"confidenceAdjustmentMeaning": "The current conservative_penalty adjustment retains the existing formula used by the shared family-fit core."
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"strategyOptions": {
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"blended": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance.",
"coverage": "Rewards stocks that activate often without giving up too much quality.",
"precision": "Prioritizes hit rate and average return after activation."
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"backendAlgorithm": "alpha1",
"universeIdentity": {
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"size": 13,
"members": [
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"scoreModeDescription": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance."
}