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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.",
    "forwardReturnMeaning": "Forward returns are measured from the close before activation through each requested horizon.",
    "profileBreadthMeaning": "Measures how much of the tested Aptet parameter grid clears a robust quality threshold after weighting for sample confidence.",
    "parameterStabilityMeaning": "Measures whether nearby Aptet parameter combinations retain a large share of the best profile's normalized quality.",
    "confidenceAdjustmentMeaning": "The current conservative_penalty adjustment retains the existing formula: rawScore * confidence + rawScore * (1 - confidence) * 0.50."
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  "strategyOptions": {
    "shadow": "Scores the stock like a standalone trade-only-when-active strategy.",
    "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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    "hash": "d5c64584c78ca8dfbeadb99e270550e2185074e11f05a4afaef39938a7b5ae45",
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      "XLV",
      "XLY"
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    "version": 1
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  "scoreModeDescription": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance."
}

{
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    "portfolioSizes": [
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    "safetyNetEquity": "VOO"
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    "scoreMeaning": "The effective fit score after applying the conservative confidence penalty.",
    "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": {
    "shadow": "Scores the stock like a standalone trade-only-when-active strategy.",
    "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": {
    "hash": "d5c64584c78ca8dfbeadb99e270550e2185074e11f05a4afaef39938a7b5ae45",
    "size": 13,
    "members": [
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      "XLE",
      "XLF",
      "XLI",
      "XLK",
      "XLP",
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      "XLU",
      "XLV",
      "XLY"
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    "version": 1
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  "scoreModeDescription": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance."
}