Progress Curve Fitting

Progress Curve Fitting

Purpose

Fit parametric curves to historical SOTA performance data, identify inflection points representing paradigm shifts, and extrapolate future progress trajectories. Produces structured data suitable for visualization and trend analysis.

Input Schema

Output Schema

{
  "dataset": "string",
  "metric": "string",
  "time_range": {"start": "string", "end": "string"},
  "sota_frontier": [
    {"date": "string", "method": "string", "score": 0.0, "is_new_sota": true}
  ],
  "curve_fit": {
    "best_model": "logarithmic|linear|sigmoid|exponential|piecewise",
    "parameters": {},
    "r_squared": 0.0,
    "residual_std": 0.0
  },
  "inflection_points": [
    {
      "date": "string",
      "method": "string",
      "score_before": 0.0,
      "score_after": 0.0,
      "jump_magnitude": 0.0,
      "paradigm_shift": "string"
    }
  ],
  "trend_metrics": {
    "annual_improvement_rate": 0.0,
    "improvement_accelerating": false,
    "years_since_last_major_jump": 0.0,
    "current_plateau_duration": null
  },
  "extrapolation": {
    "predicted_1yr": 0.0,
    "predicted_3yr": 0.0,
    "confidence_band_1yr": [0.0, 0.0],
    "confidence_band_3yr": [0.0, 0.0],
    "caveat": "string"
  }
}