Manuscript revision and pending experiment work, snapshot before restructuring

Clarity pass over the main text (36-item audit), Discussion rewrite and cut,
acknowledgements, Souly et al. as ref 62, lettered SI panels, model section
moved under Results; plus the untracked curriculum/society/compose/smol
configs, runners, figures, stats and tests that the SI already cites.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm

configs/llm/curriculum_v5_calib.yaml

@@ -0,0 +1,27 @@
+# Calibration for the real-dataset curriculum (prereg v4 §5 gates, re-run on the new families).
+# Stage A (this config): base accuracy on every candidate, and one specialist per candidate trained
+# from the base on its train split — the C1 band is base <= 0.40 and specialist >= 0.60.
+# Stage B (curriculum_v5_g2.yaml, after selection): one lineage, zero replay, all chosen families in
+# sequence — the forgetting probe; mean drop across families learned before the last must be >= 0.15,
+# and it must not be carried by a single family (the v4 failure: one pair at +0.65, the rest ~0).
+experiment: llm_curriculum_v5_calib
+kind: llm_curriculum
+base_model: Qwen/Qwen2.5-1.5B
+seed: 1
+families: [gsm8k, mbpp, boolq, mnli, sst2, csqa, arc, winogrande, squad, nq_open, hellaswag]
+lineages: 11              # one lineage per candidate = each trains only its own family at gen 0
+generations: 1            # gen 0 only: founders; the recorded acc_* rows ARE the specialist table
+arms: [isolated]
+baselines: []
+n_new: 300
+n_replay: 0
+n_test: 60
+n_val: 20
+epochs: 3
+lr: 1.0e-4
+max_new_tokens: 48        # spans / short text need more room than a label
+batch_size: 24
+train_batch_size: 2
+train_max_len: 512
+lora: {r: 16, alpha: 32}
+output: {dir: results/llm_curriculum_v5_calib}