Active ownership escalation; Schedule 13D Item 4 source-schema v3

remain forbidden; zero return identities are spent.

Why v3 is a source correction, not parser tuning

V2 used the unchanged 160-accession sample and added the SEC structured Schedule 13D schema, but the implementation required the primary bytes to begin with an XML declaration. Actual EDGAR SGML wraps structured primary documents inside an outer <XML> envelope, so all ten sampled 2025 structured filings bypassed the schema parser. One legacy submission also contained two exact-form documents; the v1/v2 parser ignored the standard SGML sequence field and therefore could not select the sequence-1 primary document.

V3 may change only these source mechanics:

1. unwrap one outer EDGAR <XML> envelope before parsing the namespaced edgarSubmission tree;
2. when multiple exact-form documents exist, retain the unique document whose SGML <SEQUENCE> is 1; and
3. retain the v2 structured item4/transactionPurpose extraction and legacy heading patterns unchanged.

No heading phrase, minimum length, active-intent classifier, ownership regex, sample row, threshold, or label is changed. The original 160 accessions remain frozen. This protocol does not replace or erase either failed result.

Unchanged machine and human gates

• 160/160 submissions succeed;
• at least 98% have one exact primary after the sequence-1 rule;
• at least 90% yield Item 4;
• every positive classification retains a source sentence;
• positive class rate remains between 10% and 90%; and
• the frozen 48-row human audit must eventually achieve at least 95% positive precision, 80% recall, and 90% exact ownership agreement.

Machine success with incomplete labels is HUMAN_AUDIT_REQUIRED, not a pass to returns. Any machine failure is DATA_GATED. The unchanged sample may be used as a source-schema regression corpus; a future return protocol still requires a disjoint untouched event holdout.

Pre-label scoring clarification: 2026-08-22

The original scorer left ownership_exact_rate permanently null, making the declared ownership gate impossible to pass even after all labels were complete. Before any of the 48 human labels was opened, the scoring contract was therefore completed as follows: the frozen machine percentage output is the sole candidate when exactly one candidate exists, and unresolved otherwise. Exact agreement requires equality to the human percentage or agreement on unresolved; there is no tolerance, inference, summation, or post-label rule selection. This clarification does not alter the regex, corpus, thresholds, classifier, or machine results and can make the gate fail.

The blind packet under artifacts/labeling/active_ownership_13d_item4_v3_blind/ contains all 48 source excerpts, an empty review sheet, a blank independence-attestation template, exact frozen labeling rules, and a standard-library-only verifier in deterministic shuffled order. The authoritative packet identity is the self-verifying content_hash in manifest.json; no copied hash in this prose may supersede it. Before labeling, the independent reviewer runs python3 verify_review.py and proceeds only on PACKET_VALID. After completing copies named completed_labels.csv and completed_attestation.json, the reviewer reruns the verifier and returns exactly those two files only on REVIEW_RETURN_VALID.

The governed importer independently verifies the manifest, source lineage, immutable row metadata, templates, completed files, and independence attestation before it can alter the canonical frozen labels. The packet and its deterministic handoff archive deliberately exclude machine classifications, matched sentences, percentage candidates, prices, and returns. Structural verification cannot itself prove reviewer independence or label correctness; those remain the reviewer's attested responsibility and the subsequent frozen scoring gate.

Prospective gate-interpretation audit: 2026-08-26

Before any human labels or return data were opened, the discrete reachability and statistical meaning of the 48-row gate were audited in docs/design/ACTIVE_OWNERSHIP_HUMAN_GATE_AUDIT.md. The existing 95% precision, 80% recall, and 90% ownership point thresholds remain unchanged. They govern eligibility to proceed to return preregistration; they do not, by themselves, establish confidence-bound classifier accuracy.

The frozen packet contains eight machine-predicted positives, so the precision point gate requires 8/8 and fails on one false positive. Even 8/8 has a one-sided 95% exact lower bound of only about 68.8%. Any passing report must therefore publish raw confusion counts, point metrics, and exact confidence bounds. Before sleeve admission, a disjoint independent confirmatory corpus must meet the same thresholds on one-sided 95% exact lower bounds. This interpretation was fixed while all 48 human labels remained blank and zero return identities had been spent; it cannot rescue a known classification or investment outcome.

Machine outputs

• artifacts/feasibility/active_ownership_13d_item4_v3/document_audit.parquet
• artifacts/feasibility/active_ownership_13d_item4_v3/frozen_human_labels.csv
• artifacts/feasibility/active_ownership_13d_item4_v3/result.json

Claim boundary

V3 can establish document extraction feasibility only. It cannot establish classification accuracy until frozen labels are complete, and it cannot establish returns, Sharpe, drawdown, correlation, capacity, or sleeve admission.