Charter v0.2: two-track structure for bigger models and J-lens (issue #1)

RESEARCH_PLAN.md

@@ -5,9 +5,9 @@
 **Project:** The Spoon Project ([README.md](README.md) holds the narrative charter; this file holds the protocol)  
 **Repository:** `VirtualVagus`  
 **Python package:** `virtual_interoception`  
-**Status:** Draft research charter v0.1  
-**Authoring date:** 2026-08-02  
-**Target machine:** MacBook Pro with 16 GB unified memory  
+**Status:** Draft research charter v0.2  
+**Authoring date:** 2026-08-02; amended 2026-08-10 for the two-track structure ([issue #1](https://github.com/BioNanomics/VirtualVagus/issues/1))  
+**Target machine:** MacBook Pro with 16 GB unified memory (local reference) plus the Purdue Gilbreth GPU cluster (Section 5.2)  
 **Authoritative workflow:** command-line programs, versioned configurations, automated tests, and Git-tracked gate decisions. No notebook is an authoritative research artifact.
 
 ---
@@ -33,6 +33,15 @@ A standard decoder-only transformer forward pass is a directed acyclic computati
 
 The strongest version of the hypothesis is not merely that bodily words influence later words. It is that the model contains a latent body-state mediator that can be causally inserted, removed, or rerouted even when no bodily words are present.
 
+### 1.2 Two research tracks
+
+Amended 2026-08-10 ([issue #1](https://github.com/BioNanomics/VirtualVagus/issues/1)): the project runs two coordinated tracks.
+
+- **Track A — interoception ladder.** The original program, on the Pythia family (Section 5). Milestones 0–11 and gates G00–G11 are unchanged.
+- **Track B — J-space connection.** Tests whether the interoceptive mediator lies inside or outside the verbalization-poised (J) subspace, on the Gemma family, where fitted Jacobian-lens artifacts and validated emotion-vector recipes provide external anchors. Milestones B1–B2, gates GB1–GB2. Method review and evidence floor: [docs/j-space-global-workspace.md](docs/j-space-global-workspace.md).
+
+Track B opens only after gate G02 closes, so the authorized `EXP-003-v2` repeat stays first. Passive J-lens readout is never gate-eligible evidence in either track (see `j_space` in [docs/glossary.md](docs/glossary.md)).
+
 ---
 
 ## 2. Hypotheses and null hypotheses
@@ -113,6 +122,9 @@ No result in this plan establishes subjective experience.
 - [ ] Large tensors and model files are content-addressed outside ordinary Git history; their manifests and hashes remain in Git.
 - [x] CPU float32 is the numerical reference path.
 - [x] MPS acceleration is used only after a parity test against the CPU reference.
+- [ ] CUDA acceleration is used only after a parity test against the CPU reference; for models exceeding local memory, the CPU float32 reference run executes on cluster CPU nodes.
+- [ ] Cluster runs execute inside a versioned Apptainer image whose digest is recorded in the run manifest.
+- [ ] Slurm batch scripts are thin wrappers around the same versioned CLI commands used locally; no cluster-only experiment logic.
 - [x] Quantized models are not used as primary causal evidence.
 - [x] A failed gate can be repeated once for a documented technical or design defect. A second failure forces a pivot or stop decision.
 
@@ -172,28 +184,49 @@ Every gate-eligible run must produce a machine-readable `run.json` containing at
 }
 ```
 
+Cluster (Gilbreth) runs must additionally record `gpu`, `cuda`, `driver`, `node_type`,
+`slurm_job_id`, and `container_digest`. These fields are null for local runs.
+
 ### 4.4 Storage policy
 
 Recommended:
 
 - Git for code, configurations, protocols, compact data, summary results, figures, and decision records.
 - `artifacts/` for local activation tensors, excluded from ordinary Git.
 - DVC or an equivalent content-addressed store for large reproducible artifacts; its metadata remains in Git.
+- Cluster scratch/Depot for fitted lenses, activation dumps, and other large Track B artifacts; only manifests and content hashes return to Git.
 - Hugging Face model cache outside the repository, with exact revisions recorded in the manifest.
 
 ---
 
 ## 5. Recommended model ladder
 
+### Track A — interoception ladder (Pythia)
+
 | Role | Model | Purpose |
 |---|---|---|
 | Unit-test fixture | TinyStories 1-layer 21M or Pythia-31M | Test hooks, tensor shapes, patching code, and CI without heavy compute |
 | Development | Pythia-70M | Rapid end-to-end experiments |
 | Primary discovery | Pythia-160M | Main small-model target with enough capacity for structured narrative relations |
-| Replication | Pythia-410M | Test whether effects strengthen or reorganize with scale |
+| Replication | Pythia-410M | Scale trend; folded into the `EXP-003-v2` behavioral repeat (G02 amendment below) |
+| Conditional scale extension | Pythia-1B / Pythia-1.4B | Registered only if the 410M scale trend is promising; runs under Milestone 9 |
 | Training-dynamics replication | Selected Pythia checkpoints and seeds | Determine emergence and seed stability |
 
-Pythia is preferred because the suite was designed for interpretability and exposes many training checkpoints. Use models sequentially, not simultaneously, to remain within 16 GB.
+Pythia is preferred because the suite was designed for interpretability and exposes many training checkpoints. Use models sequentially, not simultaneously, to remain within 16 GB locally.
+
+### Track B — J-space connection (Gemma)
+
+| Role | Model | Purpose |
+|---|---|---|
+| Track B behavioral + extraction | Gemma 2 2B | Smallest model with a validated emotion-vector recipe (EmotionScope); behavioral battery partially Mac-runnable |
+| Track B lens anchor | Gemma-4-12B | Published fitted J-lenses and preregistered reliability campaign (`solarkyle/jspace`); validates our lens machinery; cluster-only |
+
+No J-space study exists below ~2B parameters, and passive J-lens readouts are already
+indistinguishable from shuffled-corpus controls at 2–4B
+([docs/j-space-global-workspace.md](docs/j-space-global-workspace.md)). Track B therefore
+does not run on the Pythia ladder; a Pythia lens fit may be registered only as a
+negative-control curiosity, never as gate evidence. Track B revisions are pinned in
+`configs/models/` when Milestone B1 opens.
 
 ### 5.1 Memory discipline
 
@@ -205,6 +238,13 @@ Pythia is preferred because the suite was designed for interpretability and expo
 - [ ] Store analysis copies in float16 only after a float32 reference result exists.
 - [ ] Clear model and backend caches between model changes.
 
+### 5.2 Compute environments
+
+| Environment | Role | Constraints |
+|---|---|---|
+| MacBook Pro, 16 GB unified memory | Development, CI fixtures, CPU float32 reference for Track A models, MPS parity runs | Models used sequentially; Section 5.1 discipline |
+| Purdue [Gilbreth](https://www.rcac.purdue.edu/compute/gilbreth) (A100 80GB / H100, Slurm) | Confirmation-scale lens fits and control-lens suites, Gemma-4-12B work, Milestone 9 checkpoint × size × seed sweeps, CPU float32 reference for models exceeding 16 GB | CentOS 7: runs execute inside a versioned Apptainer image; `sbatch` scripts are thin wrappers around the local CLI (Section 4.1) |
+
 ---
 
 ## 6. Proposed repository
@@ -515,6 +555,13 @@ Initial preregistered continuation criteria:
 
 **STOP the loop pursuit in this model family when:** Pythia-410M also fails the behavioral prerequisite. Preserve the result as a useful negative finding or move to a different model family under a new charter.
 
+**Amendment (2026-08-10, [issue #1](https://github.com/BioNanomics/VirtualVagus/issues/1)).**
+The authorized `EXP-003-v2` repeat additionally runs Pythia-410M under the same
+preregistered thresholds, converting the repeat into a three-point scale trend
+(70M/160M/410M). The 410M thresholds must be committed before its held-out split is
+scored. A Pythia-1B/1.4B scale extension is registered only if the 410M trend is
+promising, as a new experiment version under Milestone 9.
+
 ---
 
 ## Milestone 3 — Representation mapping without causal claims
@@ -762,14 +809,15 @@ Determine whether the phenomenon is stable, scale-dependent, seed-specific, or d
 ### Checklist
 
 - [ ] Freeze the discovery protocol before replication.
-- [ ] Repeat behavioral and strongest causal endpoints on Pythia-70M, 160M, and 410M.
+- [ ] Repeat behavioral and strongest causal endpoints on Pythia-70M, 160M, and 410M; extend to Pythia-1B/1.4B only under the registered conditional scale extension (Milestone 2 amendment).
 - [ ] Repeat the primary endpoint across multiple Pythia random seeds where available.
 - [ ] Select training checkpoints before running them, for example initialization, early, middle, late, and final checkpoints.
 - [ ] Track when behavioral coupling first appears.
 - [ ] Track when separable `mobilization`/`body_state` and `action_appraisal` representations appear.
 - [ ] Track when causal mediation appears.
 - [ ] Compare layer locations using relative depth, not only absolute layer number.
-- [ ] Test one unrelated small model family only after the Pythia replication is complete.
+- [ ] Test one unrelated small model family only after the Pythia replication is complete. Track B (Milestones B1–B2) designates Gemma as that family; behavioral results from GB1 satisfy this item.
+- [ ] Run checkpoint × size × seed sweeps as Slurm array jobs on Gilbreth (Section 5.2), one manifest per run.
 - [ ] Separate failure to replicate from failure due to different tokenization or weak task competence.
 
 ### Gate G09 — Does the phenomenon generalize?
@@ -821,6 +869,67 @@ Determine whether sparse autoencoders expose interpretable features correspondin
 
 ---
 
+## Milestone B1 — Track B behavioral prerequisite and lens-machinery validation
+
+### Objective
+
+Establish the behavioral phenomenon on the Track B family and validate the Jacobian-lens machinery against published artifacts before any J-space claim about interoception. Begins only after gate G02 closes.
+
+### Checklist
+
+- [ ] Pin Gemma 2 2B and Gemma-4-12B model and tokenizer revisions in `configs/models/`.
+- [ ] Re-validate the stimulus corpus under the Gemma tokenizer: continuation tokenization normalization, banned-word coverage, and token-length balance.
+- [ ] Register G02-equivalent thresholds for Gemma 2 2B in `configs/gates/` before scoring the held-out split.
+- [ ] Run the behavioral battery on Gemma 2 2B (CUDA parity-gated or cluster CPU reference per Section 4.1).
+- [ ] Reproduce one published `solarkyle/jspace` Gemma-4-12B result with our lens-application code against their fitted lens, within a registered tolerance.
+- [ ] Fit a pilot J-lens (10–25 prompts × 128 tokens) and a token-shuffled-corpus control lens on Gemma 2 2B; record both as content-addressed artifacts with manifests.
+- [ ] Record where the shuffled control matches the pilot lens; passive readout scores are recorded as diagnostics only.
+
+### Gate GB1 — Does Track B have a behavioral phenomenon and trustworthy machinery?
+
+**CONTINUE only when all are true:**
+
+- [ ] Gemma 2 2B passes the registered G02-equivalent criteria on the held-out split, including the keyword-free subset.
+- [ ] The published-artifact reproduction matches within the registered tolerance.
+- [ ] The pilot lens is distinguishable from the shuffled-corpus control on at least one registered causal (not passive) diagnostic.
+
+**PIVOT when:** Gemma 2 2B fails behaviorally but a registered Gemma-4-12B check passes; continue Track B at 12B only.
+
+**STOP Track B when:** both Gemma models fail the behavioral prerequisite, or the machinery cannot reproduce published artifacts after one authorized repeat. Track A is unaffected.
+
+---
+
+## Milestone B2 — J-space decomposition of the interoceptive mediator
+
+### Objective
+
+Test whether the `mobilization`/`body_state` mediator lies inside or outside the verbalization-poised (J) subspace, and whether its influence on appraisal is J-mediated, using the automatic-versus-flexible design. Begins after GB1; does not depend on Track A gates because Track B extracts its own directions on the Gemma family.
+
+### Checklist
+
+- [ ] Extract candidate `mobilization`/`body_state` directions on Gemma 2 2B with an EmotionScope-style recipe (conditioned mean difference, neutral-PC removal), with embedding-only and bag-of-words baselines.
+- [ ] Fit a confirmation-scale lens (500–1000 prompts × 128 tokens) plus shuffled-corpus, disjoint-corpus, and rotated-dictionary control lenses on Gilbreth.
+- [ ] Sparse-decompose the candidate direction into J and non-J components using both the sparse-cone (gradient pursuit, registered $k \le 25$) and strict local-orthogonal decompositions.
+- [ ] Run the norm-controlled intervention matrix: full direction, J component, non-J remainder, sign reversal, norm-matched random, shuffled-lens, and rotated-J controls; report equal-coefficient and equal-norm scalings separately.
+- [ ] Run the automatic-versus-flexible battery: identical body-state evidence under (a) natural continuation, (b) explicit report of the feeling, (c) an arbitrary context-specified rule applied to the feeling.
+- [ ] Track J-space entry of injected non-J components across layers and repeat interventions under downstream J-clamping.
+- [ ] Escalate the strongest registered result to Gemma-4-12B using the published lens.
+
+### Gate GB2 — Is the interoceptive mediator inside or outside the J subspace?
+
+Either answer is a result. **CONTINUE only when all are true:**
+
+- [ ] J and non-J intervention effects are distinguishable from norm-matched random, shuffled-lens, and rotated-J controls.
+- [ ] Any off-J (bypass) claim survives downstream J-clamping; any J-mediation claim shows clamp sensitivity.
+- [ ] The automatic-versus-flexible contrast was registered before held-out scoring, and at least one predicted dissociation is observed or cleanly falsified.
+- [ ] No conclusion rests on passive J-lens readout.
+
+**PIVOT when:** decomposition components are individually inert but the full direction is causal. Report a nonlinear or distributed interaction, not a J-space localization.
+
+**STOP the J-space connection when:** interventions cannot be distinguished from matched geometric controls at either model scale.
+
+---
+
 ## Milestone 11 — Clean-room reproduction and release
 
 ### Objective
@@ -920,7 +1029,7 @@ These controls are mandatory before a loop claim.
 |---|---|---|---|
 | EXP-001 | End-to-end tooling smoke test | TinyStories 21M or Pythia-31M | G01 |
 | EXP-002 | Behavioral threat/body factorial | Pythia-70M | G02 |
-| EXP-003 | Held-out behavioral replication | Pythia-160M | G02 |
+| EXP-003 | Held-out behavioral replication (v2 adds the 410M scale point) | Pythia-160M + Pythia-410M | G02 |
 | EXP-004 | Layerwise latent-variable probes | Pythia-160M | G03 |
 | EXP-005 | Lexical and causal-attribution falsification | Pythia-160M | G03 |
 | EXP-006 | Event-to-body activation patching | Pythia-160M | G04 |
@@ -934,6 +1043,12 @@ These controls are mandatory before a loop claim.
 | EXP-014 | Training-checkpoint emergence | Pythia-160M checkpoints | G09 |
 | EXP-015 | SAE factorization | Pythia-160M | G10 |
 | EXP-016 | Clean-room release reproduction | Primary model | G11 |
+| EXP-017 | Conditional scale extension (only if the 410M trend is promising) | Pythia-1B / Pythia-1.4B | G09 |
+| EXP-B01 | Gemma tokenizer validation and behavioral battery | Gemma 2 2B | GB1 |
+| EXP-B02 | Published-lens machinery reproduction | Gemma-4-12B | GB1 |
+| EXP-B03 | Pilot lens fit with shuffled-corpus control | Gemma 2 2B | GB1 |
+| EXP-B04 | Mediator J-decomposition and intervention matrix | Gemma 2 2B | GB2 |
+| EXP-B05 | Automatic-versus-flexible interoception battery | Gemma 2 2B → Gemma-4-12B | GB2 |
 
 ---
 
@@ -1045,7 +1160,7 @@ Effects disappear under body-channel, causal-attribution, or keyword-free contro
 
 ### Outcome E — Small-model boundary
 
-The effect is absent in 70M–410M Pythia models despite adequate task competence. This establishes a scale/model boundary and motivates a separately chartered larger-model study.
+The effect is absent in 70M–410M Pythia models despite adequate task competence. This establishes a scale/model boundary; Track B (Milestones B1–B2) is the chartered larger-model continuation.
 
 ---
 
@@ -1075,6 +1190,18 @@ The effect is absent in 70M–410M Pythia models despite adequate task competenc
 8. uv project and lockfile documentation:  
    https://docs.astral.sh/uv/
 
+9. Anthropic Jacobian-lens reference implementation:  
+   https://github.com/anthropics/jacobian-lens
+
+10. `solarkyle/jspace` — Gemma-4-12B reliability campaign with published fitted lenses and traces:  
+    https://github.com/solarkyle/jspace
+
+11. `amaljithkuttamath/jlens-replication` — shuffled-corpus and truncation controls at 2–4B scale:  
+    https://github.com/amaljithkuttamath/jlens-replication
+
+12. Full J-space method review, evidence floor, and repository survey:  
+    [docs/j-space-global-workspace.md](docs/j-space-global-workspace.md)
+
 ---
 
 ## Final decision rule

docs/glossary.md

@@ -225,6 +225,29 @@ recurrent wire inside a single forward pass. See [architecture-note.md](architec
 
 ---
 
+### J-space (`j_space`) — Verbalization-poised subspace
+
+The set of sparse nonnegative combinations of Jacobian-lens dictionary directions at a
+layer — a union of low-dimensional cones, not a linear subspace. In this repository
+`j_space` means only: the region of activation space poised, on average across contexts,
+to influence future verbalization, as defined operationally by a fitted lens and a
+registered sparsity $k$.
+
+Requirements for use:
+
+- A J-space claim is causal or it is not made. Passive J-lens readout is never
+  gate-eligible evidence: token-shuffled-corpus control lenses match it at 2–4B scale.
+- Any off-J ("bypass") claim requires survival under downstream J-clamping.
+- Every fitted lens is a content-addressed artifact with a manifest, and every J-space
+  experiment fits or reuses shuffled-corpus and rotated-dictionary control lenses.
+
+"Global workspace" is **not** accepted vocabulary in this repository. It is the external
+literature's hypothesis about broadcast geometry, not a validated construct here. See
+[claim-boundaries.md](claim-boundaries.md) and
+[j-space-global-workspace.md](j-space-global-workspace.md).
+
+---
+
 ## 3. Evidence terms
 
 ### Efferent / afferent