ExtremaRank v0.2.0: paired studies, Welch and external model refits

ExtremaRank v0.2 broadens candidate-list sensitivity checks to paired studies, independent two-group comparisons, and supplied external-model refits. Study reports identify actual omitted units, candidate exits/entries, and rank changes across every feasible delete-one scenario.

• Keep the original exact paired two-family extrema and shared Top-K audit.
• Add exact Welch ranking comparisons with bounded exhaustive shared-deletion search.
• Add strict matrix/metadata joins, explicit contrasts, preparation/exclusion records, and offline diagnostic reports.
• Compare full-feature external refit tables with OBSERVED_STABLE / OBSERVED_CHANGED; an executed limma moderated-t exporter is included.

Validation: 44 tests pass locally on Python 3.12 and 3.14; 2,000 independent Welch problems pass 91,227 rank comparisons and 6,000 complete status checks. The public 38-sample / 3,051-feature Golub matrix passes 117 full-feature Fraction ranking checks. The limma adapter passes 117 Top-20 matches against R. A clean wheel installation runs all three workflows with only Python and pip installed.

Native guarantees apply to frozen finite binary64 inputs and the stated statistic. Welch does not inherit the paired theorem's speedup and can be unresolved at its limit. External comparisons cover only supplied scenarios and do not certify unobserved deletions. Proteomics/metabolomics portability is not real cross-omics validation; no FDR, clinical efficacy, prediction accuracy, or global priority claim is added.

See docs/STUDY.md and docs/UPGRADE_CN.md for formats, commands, examples and scope. Third-party source attribution and LGPL material are retained separately from the MIT software. Assets contain the full reproducibility bundle, a dependency-free wheel, and SHA256 checksums.