Table 2: add Qwen3.5-4B LoRA (#22), gemma3-270m specialist and general (#26, #27), ProKope-421M-8K (#23/#24)

README.md

@@ -108,7 +108,11 @@ model is learning the teacher's quirks.
 | [Phocinae-Largha-150M-v1](https://huggingface.co/Phocinae/Phocinae-Largha-150M-v1) (mmBERT-small, 144.3M) | specialist | 0.791◇ | – | – | – | 21.0 ms‡ (RTX 5090) |
 | [OpenDecider-medium-td](https://huggingface.co/manjunathshiva/opendecider-medium-td) (Qwen3-30B-A3B + LoRA) | general, then fine-tuned on `train` | 0.788 | 0.081 | 0.044 | – | 214 ms‡ |
 | [soft-decider-421m](https://huggingface.co/winwinwinbb/soft-decider-421m) | specialist | 0.774 | – | – | 0.141¶ | 50 ms‡ |
+| [Qwen3.5-4B-typed-decisions](https://huggingface.co/wozniakos10/Qwen3.5-4B-typed-decisions) (Qwen3.5-4B + LoRA, Clef head) | general, then fine-tuned on `train` | 0.7725 | 0.0992 | 0.0543 | 0.139¶ | – |
 | [Laya typed-decisions](https://huggingface.co/convaiinnovations/laya-typed-decisions) | fitted on `train` | 0.766 | – | – | – | – |
+| [gemma3-270m-typed-decisions](https://huggingface.co/rony/gemma3-270m-typed-decisions) (Gemma 3 270M, full fine-tune) | specialist | 0.761 | 0.132 | 0.072 | 0.148¶ | 68 ms‡ |
+| [ProKope-421M-8K](https://huggingface.co/ProKope-AI/ProKope-421M-8K) (421M, 8K context) | specialist | 0.7185 | – | 0.385§§ | – | 43 ms‡ |
+| [gemma3-270m-typed-decisions](https://huggingface.co/rony/gemma3-270m-typed-decisions) (Gemma 3 270M, full fine-tune) | general, fine-tuned on `train` | 0.702 | 0.156 | 0.091 | 0.128¶ | 68 ms‡ |
 | [Bekko System One v0 400M](https://huggingface.co/hotchpotch/bekko-system-one-v0-400m), scored by us | trained on `train` and other data | 0.668 | 0.214 | 0.113 | 0.143 | 808 ms† |
 | ModernBERT-base (149M), ours | specialist, fitted per workflow | 0.646 | 0.223 | 0.119 | 0.179 | 349 ms† |
 | MiniLM-L6 (22M), ours | specialist, fitted per workflow | 0.587 | 0.262 | 0.143 | 0.108 | 22 ms† |
@@ -117,6 +121,8 @@ model is learning the teacher's quirks.
 
 ¶ The submitter's own ECE definition, which does not match the one used above.
 
+§§ ProKope reports a multi-class vector Brier score, which is not the per-decision Brier used in the other rows, so the two are not comparable.
+
 ◇ Clean re-score by the submitter after removing 500 training pairs derived from model predictions on `test` rows ([discussion #25](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/25)). The originally submitted 0.906 was measured on a split the model had partly seen, so it is not listed; KL, Brier and ECE were only reported for that run. Do not train on `test` rows, `test` labels, or anything derived from predictions on them.
 
 **[meraGPT Decider 1](https://meragpt.com/models/state-decider-1?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=typed-decisions) is state of