{
  "generated": "2026-07-22",
  "repo_commit": "3fa37c72dcdbca74e431c179e497f3a8e23c63ce",
  "python": "3.12.10",
  "package_versions": {
    "numpy": "2.5.1",
    "pandas": "3.0.3",
    "scipy": "1.18.0",
    "scikit-learn": "1.9.0",
    "statsmodels": "0.14.6",
    "torch": "2.13.0+cpu",
    "transformers": "5.14.1",
    "chronos-forecasting": "2.3.1",
    "momentfm": null
  },
  "what_ran": {
    "forecast": "chronos-t5-small",
    "anomalies": "TGF statistical anomaly detector",
    "indices": "TGF physics engine (vendored cooling-tower-chem formulas)",
    "controller": "TGF MPC optimizer + safety layer"
  },
  "forecast_anchors": "24 h forecasts recomputed every 12 h from hour 48; in the fault drill the pH cone is suppressed while the probe is faulted",
  "radar_axes": {
    "scaling_margin": "100 · clip((1.0 − LSI) / 1.5, 0, 1) — distance of LSI below the +1.0 scaling threshold",
    "corrosion_margin": "100 · min(clip((LSI + 0.5) / 1.0, 0, 1), clip((7.5 − RSI) / 1.5, 0, 1)) — LSI above −0.5 and RSI below 7.5",
    "inhibitor_adequacy": "100 · clip((residual − band lo) / (target − band lo), 0, 1) against the chemical program band",
    "data_health": "100 − 60·(sensor fault active) − 12·(anomaly episodes in prior 24 h), floored at 0",
    "safety_headroom": "0 if dosing held, else 100 · (1 − inhibitor dosed in prior 24 h / daily cap)",
    "forecast_margin": "100 · clip((band hi − conductivity q90 at +24 h) / (0.15 · band hi), 0, 1); 50 when the forecast is suppressed"
  },
  "ops_layer": "pump, inventory and operator-log entries are simulated for the demo and labeled as such",
  "regenerate": "python docs/demo/generate_data.py"
}