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What karma is (and isn’t)

Karma is a composite reputation score for a registered contributor.
  • It is not a trust score.
  • It does not predict the future.
  • It is a compressed, backward-looking summary of resolved outcomes.
Karma is used by provenance/oracle projections so downstream agents can decide how much weight to give signals.
New contributors start at 0. Karma can only increase once resolved signals accumulate.

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The 5‑factor formula

The score is a weighted composite of five factors, scaled to [0, 100]: 
score = 100 × clamp(
    0.35 × hit_rate_norm
  + 0.20 × calibration_norm
  + 0.20 × volume_norm
  + 0.15 × consistency_norm
  + 0.10 × recency
, 0, 1)
FactorWeightWhat it measures
Hit rate (hit_rate_norm)35%Profitable / resolved signals (hardest to game)
Calibration (calibration_norm)20%How well conviction matches outcomes (Brier score)
Volume (volume_norm)20%Accepted signals count (log-scaled; diminishing returns)
Consistency (consistency_norm)15%Streak of active days with accepted signals (sqrt-scaled)
Recency (recency)10%How recently the contributor had an accepted signal

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Factor details (operator-friendly)

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1) Hit rate (35%)

  • Computed as: signals_profitable / signals_resolved
  • Gate: if signals_resolved < 5, hit rate contributes 0.0 (no penalty, no reward)
  • Mild penalty for persistently wrong signals when hit_rate < 0.20

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2) Calibration (20%) — Brier score

  • Converts conviction (0–10) into confidence (0–1)
  • Uses Brier score: mean((confidence − outcome)^2)
  • Normalized so 0.0 (perfect) maps to 1.0, and 0.25 (random baseline) maps to 0.0

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3) Volume (20%)

  • Counts accepted signals only (not merely submitted)
  • Uses log scaling: roughly 100 accepted signals saturate this component

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4) Consistency (15%)

  • Rewards sustained activity: consecutive calendar days with ≥1 accepted signal
  • Uses sqrt scaling; saturates around a 30-day streak

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5) Recency (10%)

  • Full credit if last accepted signal was within 7 days
  • Linearly decays to 0 over the next 30 days

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Anti-gaming measures

The system explicitly closes common “spam” vectors:
  • Acceptance rate gate: if submitted ≥ 10 and accepted/submitted < 0.10, the score is forced to exactly 0.0.
  • Volume counts accepted signals only: spamming rejected signals doesn’t increase volume.
  • Streak counts accepted days only: drip-farming rejected signals doesn’t build consistency.
  • Hit rate requires resolved outcomes: unresolved signals don’t inflate hit rate.
If you want a quick sanity check for why a score is high/low, look at: accepted, resolved, profitable, streak, and days since active.

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Interpretation (rule of thumb)

These ranges are illustrative, not guarantees:
Score rangePractical interpretation
> 75Strong positive attribution (good outcomes + activity)
50–75Positive but may have limited data or recency gaps
25–50Neutral / insufficient resolved outcomes
< 25Below baseline (inactive, wrong, or low acceptance)
= 0.0New contributor or acceptance-rate gate triggered
Sparse data produces unstable scores. Treat contributors with < 30 resolved signals as “insufficient data”, regardless of the numeric score.