R12 Raw-300k Future-Jacobian Workspace Longitudinal Result

Decision: FAIL. Raw 300k has a reproducible averaged future-causal transport map, but the frozen semantic workspace gate remains zero in the decisive held-out region. No J-lens coordinate swap, workspace promotion, reasoning claim, or training intervention is authorized.

1. Custody and execution

The preregistration was committed and pushed as part of 4338c49 before any raw-300k Jacobian output existed. Scientific Python, prompt seeds, source layers, target layer, evaluation board, layer-selection rule, and thresholds are unchanged from raw 200k.

Two infrastructure-only corrections were required:

• jobs 690014/690015 exited 124 in the shared Lustre Python import preflight and wrote no matrix;
• jobs 690020/690021 staged the existing hash-bound node-local Torch runtime but exited before science because that minimal runtime lacked tokenizers.

Commits e2ba68b and 735050a stage the immutable node-local runtime plus the 11 MiB hash-bound tokenizers package. They do not alter model code, Jacobian math, prompts, labels, board, or gates. The valid chain is:

The first valid job includes cold filesystem latency; prompt-level exact Jacobian passes were about 2.6--4.4 seconds once loaded. Every model parameter remained frozen.

2. Immutable artifacts

All three scientific artifacts and logs are mode 0444 on Newton. The three scientific artifacts are mirrored locally with matching SHA-256 values.

3. Frozen decision

The original three gates are:

The frozen selected layer moves from 13 at raw 200k to 25 at raw 300k. On the decisive 2,304 language/full targets:

The selected raw-300k MRR ratio is about 4.83x, but every target remains below rank 100. This is a rank-tail effect, not a usable semantic workspace. At the same layer 25, raw-200k future MRR was 0.0005352 with median rank 2,442, so the raw-300k selected result is not even monotonic under a fixed-layer comparison.

4. Geometry

The two independent raw-300k matrices are highly reproducible. Whole-matrix cosine rises from 0.9546 at layer 5 to 0.9991 at layer 28; top-16 right-subspace overlap spans 0.8619--0.9960.

Paired same-prompt raw-200k versus raw-300k matrices change materially: whole-matrix cosine spans 0.6992--0.8233. Their top-16 right-subspace overlap is still 0.7014--0.9074, indicating a persistent broad causal subspace whose exact linear map evolved during continued pretraining. Neither fact provides the missing held-out semantic readout.

5. Interpretation

This result rejects one precise hypothesis:

By 300k, raw next-token pretraining has produced a vocabulary-aligned, averaged-future-Jacobian workspace that exposes the operation and query concepts required by the frozen referential task.

It does not prove that every distributed state is absent. The diagnostic is restricted to the paper's vocabulary-aligned averaged Jacobian object and the frozen operation/query concept targets. A task-defined causal subspace could exist without naming those concepts as single tokens, and a trainable workspace could still be installed. Either successor must be preregistered and must use bidirectional donor swaps, complement ablation, random/norm-matched controls, held-out consumers, and source-deleted reuse. Reading or linearly decoding a state is insufficient.

The July 2026 workspace study explicitly says that it does not know how the workspace scales to smaller models or when it emerges during pretraining. This longitudinal result supplies Shohin's answer at 125.1M parameters through raw 300k: the exact tested semantic workspace has not emerged.