Audit artifacts for "Reviewable Japanese Can-Do Teaching Paths with AI: A Graph-Based Micro-Lesson Procedure" (ALA 16(2))

Machine-readable audit artifacts supporting the article: Špica, D., & Perak, B. (2026). Reviewable Japanese Can-Do Teaching Paths with AI: A Graph-Based Micro-Lesson Procedure. Acta Linguistica Asiatica, 16(2), 197–238. https://doi.org/10.4312/ala.16.2.197-238 Contents (repository-relative paths):- papers/ala/validation/ailt_restaurant_app_procedure_review_packet.json (sanitized: invited_emails removed; invited_count retained)- papers/ala/validation/expert_review_restaurant_ae4f9c2d_aggregate_20260504.json- papers/ala/validation/run_log.md- papers/ala/revision_v3/supplement_manifest.md- plus frozen baseline protocol / lesson-compile JSON files Evaluated case identifiers:- packet slug: ailt-restaurant-ae4f9c2d- Can-Do ID: 457abab1-d3e8-4fb7-a39e-6859378107a9- lesson timestamp (UTC): 2026-05-02T09:30:53Z- expert aggregate export: 2026-05-04- prompt pack: cando_prompt_pack.v1 The archive supports inspection of the frozen restaurant-ordering evaluation case. It does not guarantee exact deterministic regeneration of every model output, because resolved provider/model/version were not recorded for every call. No access restrictions. Expert responses are anonymized as Reviewer_1–Reviewer_4.