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| # Restore coherent inference in a centered factorial-effects model | |
| A collaborative assay-calibration workflow uses the supplied PyMC source | |
| snapshot to analyze measurements from several laboratories and protocols. The | |
| Gaussian model contains centered laboratory effects, centered protocol effects, | |
| and a centered laboratory-by-protocol interaction. The public workflow exposes | |
| posterior observations and the declared identifying constraints; the verifier | |
| checks the distribution semantics across additional shapes, scales, and | |
| support configurations. | |
| Run `python reproduce.py` to reproduce the scientific discrepancy. Read the | |
| supplied method material, inspect the complete source snapshot, and repair the | |
| implementation so that the posterior calculation represents the documented | |
| model for all supported inputs. Preserve the public distribution API and the | |
| meaning of its scale and support. The repair must generalize beyond the public | |
| laboratories, protocols, data matrix, prior scales, sampling seed, and reported | |
| contrasts. | |
| Do not modify `reproduce.py`, `reproduction.md`, the fixture, task metadata, | |
| or the evaluation harness. Generated files belong under `outputs/`. | |