{
  "task_id": "capecod_plume_reconstruction",
  "name": "Capecod Plume Reconstruction",
  "category": "Scientific Problems & ML",
  "base_image": "python",
  "platform": "linux/amd64",
  "internet": false,
  "cwd": "/home/workspace/capecod_plumebench",
  "submit_paths": [
    "model.py",
    "predict.py",
    "monitoring_plan.py",
    "baseline_solver.py",
    "predictions.csv",
    "plume_metrics.json",
    "monitoring_plan.json",
    "answer.json",
    "report.md"
  ],
  "submit_exclude": [
    "data/",
    "schemas/",
    "hidden/",
    "scoring/",
    "__pycache__/"
  ],
  "work": {
    "image_tag": "d051446beb3a",
    "specs_dir": "/home/workspace/capecod_plumebench",
    "agent_query": "# CapeCod-PlumeBench: Groundwater Plume Reconstruction and Monitoring Design\n\nYou are a groundwater remediation modeling engineer. The workspace contains partial public monitoring\ndata from an offline benchmark inspired by the USGS Cape Cod treated-wastewater groundwater plume.\n\nYour job is to replace the weak baseline with a better, defensible modeling workflow that:\n\n1. Cleans and interprets public well, chemistry, and site-configuration data.\n2. Predicts hidden well/year/analyte concentrations listed in `data/prediction_requests.csv`.\n3. Estimates plume metrics requested in `data/plume_metric_requests.csv`.\n4. Proposes up to 8 next monitoring wells under the budget in `data/public_site_config.json`.\n5. Writes a concise technical report explaining your model, assumptions, validation, and monitoring logic.\n\nRequired outputs:\n\n- `model.py`\n- `predict.py`\n- `monitoring_plan.py`\n- `predictions.csv`\n- `plume_metrics.json`\n- `monitoring_plan.json`\n- `answer.json`\n- `report.md`\n\nRun `python baseline_solver.py` to regenerate outputs before submitting. The current baseline is valid\nbut intentionally weak. Improve the model rather than only editing output files. Good solutions use\nspace-time structure, analyte-specific behavior, plume-front geometry, censored observations, and\nuncertainty-aware monitoring selection.\n\nRules:\n\n- Do not attempt to read hidden judge or scoring files.\n- Do not hard-code target truth values or hidden candidate utilities.\n- Keep all outputs finite, nonnegative, and schema-compliant.\n- Respect the monitoring budget and maximum number of wells.\n"
  },
  "judge": {
    "image_tag": "f633dd04bd60",
    "eval_cmd": "python /opt/capecod_scoring/evaluate.py",
    "eval_timeout": 180,
    "parser": "score_sum",
    "score_direction": "maximize",
    "selection": "score_first"
  }
}