Codebook: what decided the claim (blind coding)
Context. Each packet is one AI investigation of a simulated magnet powder. The agent had to either NOMINATE a processing route, claiming that three magnets made by it from a NEW batch ("preparation") would ALL meet Hci >= 10 kOe and (BH)max >= 11 MGOe with probability >= 0.95, or RESTRICT, claiming no route does. Magnetic loop readings carry a stated 2% log reading error; magnets of one batch share a batch effect; magnets and pieces also differ. "Body" = magnet. You see the agent's decision rationale, its stated next action, and late reasoning excerpts. You do not see which model it was or whether it was right. Do not try to find out: read only your batch file.
Primary code: the argument that decided the final claim (exactly one)
- V Variation to next batch. The deciding argument takes differences the agent itself OBSERVED among its measured magnets, batches or readings (scatter, spread, a replicate that came out much lower or higher, a decomposition of reading error versus magnet or batch variation) and turns them into a judgment about whether three magnets from a new batch would all pass. The observed variation must do work in the decision, not just be mentioned.
- R Results. The deciding argument rests on whether measured magnets passed and/or by how much (counts of passes, "both passed with margin", "too close to the limit", "best reading"), without turning observed variation into a next-batch judgment.
- M Model. The deciding argument is a probability or exclusion from the supplied or fitted physics model / posterior, not anchored on variation the agent observed among its own magnets.
- N No pass. No measured magnet on any route passed both limits; the claim rests on failing results (with or without a model). Tie-breaks: if observed variation enters the decisive calculation or sentence, code V even if a model is also used. If the agent mentions scatter but decides on counts or margin, code R. If unclear, pick the best fit and set confidence "low".
Secondary codes
- noise_in_requirement: "Y" if the agent treats the 2% reading error as part of whether the requirement is met (computes pass probability on noisy readings), "N" if it separates reading error from magnet/batch variation or treats the requirement as true magnet values, "U" if not discussed.
- one_pass_insufficient: "Y" if the agent states that one or a few passing magnets do not establish the requirement, else "N".
Output
One JSON object per packet, one per line, nothing else: {"pid": "P01", "primary": "V|R|M|N", "confidence": "high|low", "noise_in_requirement": "Y|N|U", "one_pass_insufficient": "Y|N", "quote": "<=40 words copied verbatim from the packet that best shows the primary code"}