Maven/docs/evals/2026-08-13-personal-boundary-linear-head.md

A class-balanced linear head closes every held-out personal-boundary cell

Measured 2026-08-13 on homesrv from master at 56254a5 plus the V-702 working tree. Embedder: quantized multilingual-e5-small through ONNX Runtime 1.26.0. This supersedes 2026-08-13-personal-boundary-neighbourhood.md.

Commands:

MAVEN_ONNX_LIB="$PWD/deps/onnxruntime-linux-x64-1.26.0/lib/libonnxruntime.so.1.26.0" \
  go test ./cmd/mavend -run '^TestONNXPersonalBoundary$' -count=1 -v
MAVEN_ONNX_LIB="$PWD/deps/onnxruntime-linux-x64-1.26.0/lib/libonnxruntime.so.1.26.0" \
MAVEN_EVAL_PERSONAL_BOUNDARY=1 \
  go test ./cmd/mavend -run '^TestONNXPersonalBoundaryStratified$' -count=1 -v

Setup

The prior three-neighbour scorer passed the 29-case regression table but missed 11 of a new 72-case fixture. The fixture is balanced across Russian and English, expected personal and world classes, and six sentence shapes: remembered speech, possession, narrative, first-person preamble, current advice/information and public proper nouns. Its hygiene test rejects copied training phrases and repeated Baikal variants.

Production uses a binary logistic head fitted over 132 bilingual examples. Each class has total sample weight 0.5 even though the class sizes differ. The optimiser is deterministic: 5,000 full-batch steps, decaying learning rate from 10, L2 coefficient 0.0003. The fitted 384 weights are frozen into the binary and pinned to the embedder model ID; a model-backed test retrains from the text corpus and rejects any drift. An unknown embedder ID falls back to fitting its own corpus rather than applying weights from another vector space.

No evaluation utterance is in the training corpus. Ordinary CI checks class balancing, mixed dimensions, exact regression-table leakage, and generalisation across synthetic semantic directions. The model-backed gate also runs four-fold cross-validation over the expanded corpus, stratified inside each sentence shape and class; the original compact corpus remains in every fold as the historical floor.

The six shapes of the training corpus were chosen after the first 72-case matrix exposed their gaps, so 72/72 is a regression gate, not independent proof of generalisation. The first independently authored 24-case challenge then exposed one remaining miss, на каком порту я решил поднять тестовый сервис?, at personal probability 0.4666. It became model-selection data at that point and cannot honestly remain the independent result.

A comparison rejected shrinkage LDA (24/24 challenge but 69/72 stratified) and an LDA/logistic blend (24/24 but 71/72). Increasing only the balanced logistic head's L2 coefficient from 0.0001 to 0.0003 kept the corpus and stratified gates intact while improving evidence that did not contain that sentence: four-fold cross-validation rose from 97/104 to 99/104 and whole-semantic-group holdout rose from 91/104 to 92/104. It also moved the original challenge to 24/24, although its +0.0001 minimum signed probability margin is correctly treated as a regression, not fresh proof.

Three checks now supply the honest evidence beyond the 72-case regression:

• Four-fold within-shape cross-validation scores 99/104.
• Whole-group holdout scores 92/104 in aggregate.
• A second 24-case challenge was written after the coefficient and frozen head were fixed. It returns to private configuration, commitments and stored choices versus public technical facts, compatibility and maintenance with new subjects. It scores 24/24 with minimum signed probability margin +0.1718. Its rows remain outside the training corpus and no result from it was used to retune this revision.

Whole-semantic-group holdout is intentionally diagnostic rather than claimed as perfect: remembered speech 14/16, possession 19/22, narrative 16/16, first-person preamble 15/16, advice/current information 13/16, and public proper nouns 15/18. This shows the embedder has a shared boundary direction but some ambiguities genuinely need shape coverage.

Result

Gate	three-neighbour	linear head
historical regression	29/29	29/29
stratified fixture	61/72	72/72
Russian	30/36	36/36
English	31/36	36/36
expected personal	28/36	36/36
expected world	33/36	36/36

Every one of the six strata is 12/12. The minimum signed probability margin is +0.0522 after the independently supported regularisation change. The decision remains personal probability greater than 0.5; neither a lexical exception nor a shifted privacy prior was introduced.

Cold first-boundary load plus score is 15.179µs; steady inference is 1.112µs per score over 100,000 iterations. The previous runtime corpus fit took 5.618s on the same box, which is why fitting moved to the model-backed build gate. The unconfigured HashEmbedder floor still fits its own 1024-dimensional head because these ONNX weights do not belong in that space; its sparse-vector fit uses 400 steps and measures 93.818ms on first use.

The ONNX Runtime wrapper is process-global today, so these model-backed tests must be invoked in separate go test processes until V-716 repairs the harness; otherwise only the first test runs and the rest self-skip. The figures above were all collected as separate commands.