jspace/paper-D/PLAN.md

Paper D — The Verbalizable Workspace, Reproduced Across Scale and Architecture

One-sentence claim. The J-lens/global-workspace findings reproduce on gemma-4 at 2B-effective, 12B dense, and 26B MoE — readouts and regime structure transfer robustly, exact averaged Jacobians are computable through a top-8 router — but the write basis migrates with scale (token-embedding writes at 2B, activation-derived vectors at 12B+), which the original account does not predict.

Audience/venue. TMLR (reproduction/analysis) or ReScience; alternatively an interp workshop. Lowest-effort paper: ../RESULTS.md is ~85% of it. Foundation citation for Papers A and B.

Claims and evidence manifest

#	claim	evidence	status
D1	Readout reproductions (unspoken concept, cross-lingual, staging) at all three scales; strongest at 26B-MoE (spider P=1.0)	results{,-12b,-26b}/heat_*.pt, exp1 logs	✅
D2	Regime structure (transduction/sensor/workspace/motor) at all scales; fractional deepening at 12B; flatter/diffuse at MoE (J-space R²≈0)	regimes*.pt, exp4 logs, results/regimes_montage.png	✅
D3	Methodology: exact per-prompt Jacobians via batched VJPs; exact through 128-expert top-8 routing (identity anchor 0.0); costs documented	scripts/compute_jacobians.py, jbar checkpoints, timing logs	✅
D4	Write-basis migration (the novel finding): J-lens vectors read but never write; token-embedding writes 6/30+broadcast at 2B, 0/30 at 12B/26B; activation-derived vectors 30/30 at 12B and 26B — migration tracks scale, not architecture	swap_grid.pt (all three), exp2 logs	✅
D5	Directed modulation only clearly present at 26B (citrus P=0.69)	exp logs	✅
D6	Lens gate (where-to-intervene) transfers unchanged across all three	swap experiments	✅

Missing / decisions

1. No new experiments required. Optional strengthener: the un-run 31B dense scaling point (~24–30h Spark or ~4–5h on a rented node) — decide only if a reviewer asks; the 3-model story stands.
2. Verify all claims against raw artifacts during rewrite (numbers in RESULTS.md were written incrementally; re-derive tables from .pt files — scripts/stats_pass_d.py to emit paper-D/tables/).
3. Frame relationship to the original paper precisely: which claims reproduce (readouts, regimes, gate), which do not (J-lens-basis writes), and the migration as a boundary on the original's intervention story.
4. Ethics/limitations: single model family; prompt-set sizes (150/100 prompts for J̄ at 12B/26B); MoE regime flatness may be estimator noise.

Outline

1. Intro: why reproduce; what the workspace claims are.
2. Methods: lens, exact VJP Jacobians (incl. MoE router handling), corpora.
3. Reproduction results per scale (readouts, regimes) — montage figure.
4. The write-basis migration (main figure: swap grids across scale).
5. What transfers and what doesn't; implications (feeds Papers A/B).
6. Repro details: costs, seeds, artifacts (all .pt files + bucket links).

Work plan

• Re-derive all tables from artifacts (half day).
• Rewrite RESULTS.md → paper-D/draft.md in reproduction-paper voice (claims of original ⇄ outcome table up front).
• Figures from existing .pt/pngs; regenerate montage at print quality.
• Ship first — it is citable groundwork for A and B and needs no GPU.