semanticfa 0.1.1

• Bundled data upgrade: data(big5) now ships 50 x 4096 Qwen3-Embedding-8B item embeddings (rounded to 4 decimal places), replacing the 50 x 384 all-MiniLM-L6-v2 sentence-BERT embeddings of 0.1.0. Analyses run on the bundled data will differ from 0.1.0.
• sfa_item_fit() now compares candidates against unflipped (topical) construct centroids, matching sfa_anchor() and sfa_simplify(). The previous behavior sign-flipped reverse-keyed reference items into anti-topic vectors, which depressed the item-similarity profile of constructs with many reverse-keyed items and could misassign candidates. reverse_key = TRUE still flips the candidate itself.
• sfa_congruence()’s disattenuated metric now returns NA with a warning when either similarity matrix’s split-half reliability is not positive (e.g., the checkerboard sign pattern of atomic_reversed), instead of failing with an unhelpful error.
• sfa_nli_matrix() reads the entailment/contradiction label order from the cross-encoder’s model config instead of assuming the cross-encoder/nli-* order, so non-default NLI models score correctly (a warning falls back to the default order when the config is unavailable).
• sfa_parallel() now applies Horn’s sequential retention rule (count leading eigenvalues until the first falls below its null percentile) instead of counting all eigenvalues above their pointwise percentiles, and its documentation cites the embedding-benchmark precedent (Garrido et al.).
• sfa_dimselect() default encoding is now "atomic", matching sfa().
• Fitted objects store the encoded item vectors as $transformed_embeddings (previously $embeddings, which was easy to confuse with $input_embeddings).
• digest moved from Suggests to Imports: embedding cache keys are now always SHA-256 (the previous fallback hash could collide).
• Documentation fixes: sfa_anchor() help no longer claims items are sign-aligned before anchoring (they never were in this release line, by design), the big5 item-code range reads E1–O50, the README encoding table marks atomic as keying-free, and README/vignette references to the bundled data name the Qwen3 embeddings.

semanticfa 0.1.0

• Initial release.
• Core sfa() function for semantic factor analysis.
• Encoding methods: atomic_reversed, atomic, squid, mean_centered_pearson.
• Embedding-adapted parallel analysis (sfa_parallel()).
• Unified retention diagnostics (sfa_nfactors()).
• Fit diagnostics: KMO, TEFI, RMSR, CAF, McDonald’s omega, DAAL.
• Comparison metrics: Tucker phi, NMI, ARI, Frobenius, disattenuated (sfa_congruence()).
• Embedding backends: sentence-BERT, OpenAI, custom functions, precomputed.
• Bundled IPIP Big Five 50-item dataset with sentence-BERT embeddings.