Add ProKope-421M-8K (Alan Canto) to Table 2 (71.85% acc, 8K context)

This PR adds **ProKope-421M-8K** (conceived and engineered by **Alan Canto**) to Table 2 (Fitted or fine-tuned on `train`), referencing benchmark discussion [#23](https://huggingface.co/datasets/LocalLLaMA/typed-decisions/discussions/23).

- **Model Repository:** [ProKope-AI/ProKope-421M-8K](https://huggingface.co/ProKope-AI/ProKope-421M-8K)
- **Creator & Lead Architect:** **Alan Canto**
- **Framework Architect:** Wesley Foreman
- **Architecture:** 421.3M Non-Autoregressive Decision Engine (ModernBERT-large + Geodesic SLERP Multi-Head)
- **Context Capacity:** 8,192 Tokens (Full Enterprise Window)
- **Mode:** Specialist (fine-tuned on `train` split, single forward pass, 0 output tokens)
- **Verified Metrics (400 cases / 2,000 decisions):**
- Accuracy: `0.7185` (71.85% — 1,437 / 2,000 correct)
- Boolean (`noul`) Accuracy: `0.8050` (483 / 600)
- Brier Score: `0.3847`
- ECE: `0.4302`
- Latency: `42.94 ms/dec` (sub-25ms single-decision pass)
- **Artifacts:** Verified `.eval_results/typed-decisions.yaml`, `benchmark_scorecard.json`, and all 2,000 `eval_predictions.jsonl` are live in the model repository.

README.md

@@ -109,6 +109,7 @@ model is learning the teacher's quirks.
 | [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‡ |
 | [Laya typed-decisions](https://huggingface.co/convaiinnovations/laya-typed-decisions) | fitted on `train` | 0.766 | – | – | – | – |
+| [ProKope-421M-8K](https://huggingface.co/ProKope-AI/ProKope-421M-8K) (421M, Alan Canto) | specialist | 0.719 | — | 0.385 | 0.430† | 43 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† |