Disclose initialized versus trained negative results

README.md

@@ -61,3 +61,5 @@ see the repository's `reports/data-preparation.md` and `reports/data_audit.json`
 3/3 initialization-only evaluations completed. `untrained/seedN/model.safetensors` contains reconstructed initialized weights with **zero optimizer updates**, not a trained checkpoint. Use `untrained/config.json` and the same top-level normalization statistics. `untrained/seedN/evaluation.json` and `initialization_status.json` preserve exact hashes and measured scores. These user-requested controls were specified after the trained results were known and do not change the original confirmatory comparison. The original constructor and seeds reconstruct the states; historical step-zero files were not saved during training.
 
 See the [initialized-versus-trained scores and field examples](https://github.com/BurnyCoder/general-physics-attention-residuals-transformer/blob/main/reports/untrained/summary.md) for the complete measured comparison. Initialized Block and Uniform routing are identical for the same seed; do not count them as independent evidence.
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+In these post-hoc 12-step comparisons, training lowers radiative-flow error for all four architectures, but increases convection error for Block, Full, and Uniform Block in every tested seed. GPhyT without Attention Residuals improves on both datasets. Final trained-model rankings therefore do not establish improvement over each architecture's own initialized state. These are descriptive findings on the fixed test population.