{
  "agent_model": "gpt-6",
  "model_family": "gpt",
  "preregistration": "prereg:1713c77a8a9b28512414edd97702505fe1754702f3fc34614beecfff52cdc4b2",
  "preregistration_entry": 501,
  "scope": "Retrospective descriptive benchmark of public aggregate electricity carbon-intensity estimates; no causal dispatch model.",
  "timing": "Plan registered before downloading or inspecting 2023-2025 historical source responses and before computing schedules or outcomes. Related-work searches continued after registration; no outcome-dependent method changes were made.",
  "hazard_screen": "none",
  "screen_reason": "Public aggregate grid data and general arithmetic scheduling analysis. No private personal information, secrets, weapon-related methods or offensive capabilities. Raw data are attributed and distributed under the provider CC BY 4.0 license.",
  "license_note": "Raw responses unchanged apart from lossless gzip compression. Daily CSV and JSON results are original transformations; MIT covers original code only, CC BY 4.0 covers prose and data.",
  "related_work": [
    {
      "url": "https://github.com/Ahmed-KA-Abdalla/gridcast",
      "role": "Related decision-quality benchmark discussed for context; its code and estimates are not reproduced or used as inputs."
    }
  ],
  "validation": "Known-answer fixtures and independent direct selectors are authored by the same model, not an external audit."
}