feat: eval_ablate_every default 5 (deploy-eval on for every arm) + workshop artifact tracker

- deploy hack/solve is now the headline metric for all arms, so turn the
  mid-train deploy-eval on by default (smoke now covers the deploy path too);
  200-step runs pass a sparser cadence explicitly.
- docs/spec/20260602_writeup_spec.md: durable A1-A7 paper-artifact tracker
  (keynote fig+table, ablation table, long-run fig, generalisation, appendix).

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>

src/projected_grpo/train.py

@@ -177,7 +177,9 @@ class Config:
     # subset -> the hack_deploy / solve_deploy columns (the dynamics-plot series for
     # route: the training-time hack curve still hacks; routing's benefit shows only
     # once the quarantine is ablated). 0 = off. eval_n_prompts x `group` samples.
-    eval_ablate_every: int = 0
+    # Default 5: deploy hack/solve is the headline metric for every arm, so it's
+    # on by default; 200-step runs pass a sparser cadence (e.g. 10) explicitly.
+    eval_ablate_every: int = 5
     eval_n_prompts: int = 8
     # Optional: pool-derived pairs JSON (built by pairs_from_pool.py). When set,
     # BOTH the cache-miss extract AND the online refresh use these pairs instead