{
 "license": "SI-IQ values, ranks and intervals: CC BY 4.0 (IQ of SI); input scores and prices keep their sources' licences (see /data/LICENSES.md)",
 "attribution": "Aider polyglot leaderboard data (Apache-2.0); Arena leaderboard dataset on Hugging Face (CC BY 4.0); Berkeley Function Calling Leaderboard, Gorilla project (Apache-2.0); Epoch AI, ‘Capabilities & benchmarking’ (CC BY 4.0); API list prices via LiteLLM's price table (MIT); each price links to the developer's pricing page; Source: OpenRouter (openrouter.ai), licensed under CC BY 4.0: reuse and republish with attribution to OpenRouter.",
 "method_version": "1.0.0",
 "calibration": {
  "calibrated_at": "2026-10-18T16:18:22Z",
  "calibration_id": "a75ecba7e64a",
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 "constants": {
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  "iq_sd": 15.0,
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 "formulas": {
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  "weight": "w = omega * f / (sigma2 + v)",
  "theta": "D = lambda + sum(w*alpha^2); theta0 = sum(w*alpha*(y - beta)) / D; theta = (theta0 - shift) / scale",
  "se": "se = kappa * sqrt(sum(w^2*alpha^2*(sigma2 + v))) / D / scale",
  "si_iq": "SI-IQ = 100 + 15*theta (displayed: Python round(), nearest integer); 90% interval = SI-IQ +/- 1.644854*15*se",
  "domain": "theta_d0 = (sum_{b in d} w*alpha*(y - beta) + 1*theta0) / (sum_{b in d} w*alpha^2 + 1); theta_d = (theta_d0 - shift) / scale; se_d = kappa*sqrt(sum_{b in d} w^2*alpha^2*(sigma2 + v)) / (sum_{b in d} w*alpha^2 + 1) / scale"
 },
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  "qwen2-5-max",
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  "qwen3-235b-a22b-thinking-jul-2025",
  "qwen3-30b-a3b",
  "qwen3-30b-a3b-instruct-jul-2025",
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 ],
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