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gp3ml 0.3.2 — release candidate (not published)

October 2026 documentation and reproducibility

Adds a non-exported grouped-versus-row holdout leakage audit, synthetic paired-ledger visualizations, and deterministic tests. No exported ML API or transportability guarantee is changed.
Release gate: complete exact-source R CMD check –as-cran, review installed source tarball and cross-platform tests, audit publication metadata, then publish an immutable GitHub tag and submit to CRAN with maintainer confirmation.
Current CRAN baseline at candidate preparation: 0.3.0. The candidate has not been submitted to CRAN or published as a GitHub Release.

gp3ml 0.3.1

Documentation and release maintenance

Added the September 2026 ecosystem methods update and registered it in the pkgdown article navigation and article index.
Refreshed the generated public documentation and website metadata since the 0.3.0 source release.
Preserved the established scientific implementation, public API contracts, governance semantics, and backward compatibility; this patch release does not add or alter R modelling logic.

gp3ml 0.3.0

CRAN availability and metadata

Added the canonical CRAN package page, CRAN installation instructions, package-status badge, and CRAN package DOI following publication of gp3ml 0.1.0 on CRAN.

Next-generation governed research-ML infrastructure

Added explicit decision-rule contracts, threshold evaluation, deterministic threshold selection, and abstention auditing without hidden threshold defaults.
Added target-aware split-conformal calibration for regression intervals and binary prediction sets, with explicit calibration-unit and generalization-target semantics.
Added predictor-distribution and missingness-shift audits that remain distinct from prevalence, calibration, and performance drift.
Added frozen analysis-plan contracts with SHA-256 locking and post hoc deviation auditing.
Added portable model artifacts with optional bundle support, serialization validation, and optional fresh-process checks through callr.
Added robustness and stability diagnostics across seeds, features, thresholds, and missingness scenarios.
Added environment capture/comparison, minimal RO-Crate-oriented research-object export, SHA-256 release manifests, and a manual GitHub release-attestation workflow.
Added gp3ml-native, NIST AI RMF 1.0, ISO/IEC 23894-oriented, and ISO/IEC 42001-oriented governance evidence profiles. Standards-oriented outputs explicitly do not claim certification or conformity.
Added six new development articles covering decision governance, conformal prediction, dataset shift and robustness, frozen analysis plans, portable research artifacts, and governance standards crosswalks.
Added an explicit API-stability registry, public-object schema audit, and contract validation for the established 0.2.0 surface.
Added lightweight cross-package handoff contracts for gp3tools, gpbiometrics, gp3sequences, study-design data, and custom prepared data without duplicating upstream preprocessing.
Added deterministic documentation-output controls plus audits for volatile timestamps, temporary paths, and runtime addresses.
Added engine capability auditing and a Windows/macOS/Linux optional-engine CI matrix.
Added a realistic synthetic three-package research handoff and governed participant-generalization validation workflow.
Added five package-maturity vignettes covering API contracts, interoperability, reproducibility, portability, and integrated workflow validation.

gp3ml 0.2.0

Grouped evaluation and governed tuning

Added fold-local evaluation across materialized gazepoint_group_folds, with retained predictions, metrics, exclusions, leakage audits, warnings, and failures.
Added explicit deterministic tuning grids, candidate comparison, and human-reviewed selection requiring a predeclared metric and direction.
Added nested grouped resampling with inner tuning isolated inside every outer analysis partition.

Target-aligned uncertainty

Added observation, participant-cluster, stimulus-cluster, and participant-and-stimulus bootstrap uncertainty with the resampling unit recorded explicitly.
Added fold- and repeat-distribution summaries without relabelling row-level results as cluster-level estimates.

External validation and reporting

Added independent-dataset declarations, schema checks, predictor availability, prevalence shift, calibration drift, participant/stimulus coverage, and transportability limitations.
Added explicit not_externally_validated status when no independent dataset is available.
Added release-ready model cards recording selection procedures, uncertainty units, transportability status, limitations, and human oversight.

Vignettes and validation

Added nine deterministic synthetic vignettes covering recording quality, assigned conditions, observed outcomes, participant and stimulus generalization, simultaneous participant/stimulus generalization, contaminated manifests, nested resampling, and external validation.
Added focused tests, an end-to-end smoke test, a full validation driver, and a read-only 0.2.0 release audit.

gp3ml 0.1.0

First formal release

Established gp3ml as a governance-first package for leakage-resistant predictive modelling and validation using Gazepoint-derived research data.
Restricted supported tasks to explicitly observed, non-sensitive outcomes and clearly declared scientific purposes.
Added explicit prohibited-use documentation covering identification, authentication, diagnostic, protected-attribute, emotion, stress, personality, deception, cognition, comprehension, intent, and other mental-state inference.

Governance, provenance, and leakage protection

Added task declaration, use-case assertion, variable-role validation, and machine-readable prohibited-use helpers.
Added feature-provenance manifests covering predictor origins, transformations, availability stages, roles, and preprocessing scope.
Added structured leakage audits for row, participant, participant-trial, stimulus, identifier, target-derived, and post-outcome risks.

Group-aware validation

Added deterministic group-aware holdout splitting and repeated grouped resampling for new trials among known participants, new participants, new stimuli, and simultaneous new-participant and new-stimulus generalization.
Materialized analysis, assessment, and explicitly excluded partitions with complete source-row accounting and embedded leakage audits.
Added fold-balance, coverage, exclusion, and outcome-representation diagnostics with structured pass, review, and fail findings.

Governed modelling core

Added fold-local preprocessing objects with separate fitting and baking interfaces.
Added governed model engines, explicit black-box integration, classification and regression metrics, calibration assessment, and explicitly labelled bootstrap metric uncertainty.
Added external-validation evaluation and reporting without treating an internal holdout as external validation.
Added model cards and reproducibility reports that record task purpose, governance decisions, model settings, performance, calibration, uncertainty, limitations, and reproducibility information.
Model selection remains explicit and reviewable; the package does not perform autonomous black-box winner selection.

Documentation and quality assurance

Added machine-readable CSV, Markdown, and JSON reporting interfaces where supported by the relevant object.
Added deterministic synthetic tests across supported generalization targets, governance failures, leakage cases, model engines, metrics, calibration, reporting, and serialization.
Added complete pkgdown reference organization for the first formal release.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.