# Brief — Appendix B (search strategies and sources) and Appendix C (mathematical derivations) — files manuscript/appendices/appB_search_and_sources.tex, appC_derivations.tex

Follow agents/briefs/WRITER_COMMON.md. Files start with \section{...} (inside \begin{appendices}).

• Appendix B (≈ 8–12 pages): the exact acquisition procedures as executed — read ingestion/*.py, data/raw/README.md, reports/PHASE0_FEASIBILITY.md, RESEARCH_PLAN.md §2–3, manuscript/sections/part03_data.tex (do not repeat its prose; this appendix is the operational record). For each source: endpoint/bucket, release/version, filters (OpenAlex field 17 rule, year range, id-set second pass, API increment slicing by day × primary-CS/non-CS, arXiv OAI set and windows, ACL export, DBLP dump + DTD), rate limits and budgets, licence, integrity checks (manifest totals, SHA-256 per file, MD5), what was NOT obtained (Semantic Scholar, OpenAlex key, full texts), and the equivalent of a PRISMA-S search record. Include a table of exclusion codes E1–E7 with their SQL predicates paraphrased, the keep/hard-exclude type lists and the generic-deposit list (from systematic_review/define_corpus.py), and the linkage cascade with its thresholds.
• Appendix C (≈ 10–14 pages): derivations and proofs referenced by Part IV (manuscript/sections/part04_methodology.tex — read it first and match its notation): (i) the ITS model as a regression with the HAC covariance estimator and the placebo p-value as a rank statistic; (ii) Bai–Perron dynamic programme: SSR additivity, the recursion, complexity O(n² m), BIC and LWZ criteria as implemented in econometrics/structural_change.py; (iii) PELT cost and pruning condition, penalty 2σ² log n; (iv) BOCPD: Normal–Inverse-Gamma conjugate updates, Student-t predictive, run-length recursion, the fact that with a constant hazard the mass on r=0 equals H (hence the MAP-run-length detection statistic used in the code); (v) Gini as a rank formula and its equivalence with the Lorenz definition; (vi) Rao–Stirling and Leinster–Cobbold (q=2) identity; (vii) Newman–Girvan modularity for directed weighted graphs; (viii) Krippendorff's α with MASI distance; (ix) the multi-label score rule and the tie-break as a total order; (x) the emerging-topic label and why the feature construction is look-ahead-free (formal statement in terms of filtrations). Derivations must be correct and self-contained; cite the original sources (verify any new citation; most keys exist in manuscript/references.bib and references_part04.bib — reuse them).