Reproducibility Package for: Human-Study Dataset and Reproducibility Package for Staged Multi-Criteria Disclosure in ML Model Selection

This record documents the underlying human-study dataset and reproducibility materials for a staged multi-criteria disclosure study in ML model selection. The archived materials were prepared by Adil Joldić and Nina Bijedić and support multiple derived publications based on the same broader study, with version-specific processed files corresponding to different analytic snapshots and paper-level analyses. The record includes processed study data, frozen policy and stimulus specifications, and reporting artifacts needed to verify published analyses. It does not include the full live study application or the complete agent system codebase; instead, it focuses on the processed study data, frozen scenario specifications, and analysis artifacts required for paper-level reproducibility. Derived publications based on this broader study include: Joldić, A., Bijedić, N., Gašpar, D., & Mabić, M. (2026). From Unaided Choice to Multi-Criteria Disclosure: A Human Study of ML Model Selection in Higher-Education Quality Assurance. ISDA 2026. Joldić, A., Bijedić, N., & Gašpar, D. (2026). Behavioral Evidence from Staged Multi-Criteria Disclosure: A Companion Human-Study Analysis of ML Model-Selection Deliberation in Educational QA. ICIICE 2026. Joldić, A., & Bijedić, N. (2026). Human-Centred Acceptance and Selective Reliance in AI-Assisted Decision Support for Higher-Education Quality Assurance. TILE-TEC 2026. This archived version corresponds to the locked public reproducibility snapshot tied to export 20260314_003853Z. It represents the paper-level frozen dataset package used for confirmatory and sensitivity analyses reported from that snapshot, including the ISDA 2026 paper and companion analyses derived from the same broader study. The locked snapshot contains: 38 participants / 228 confirmatory scenarios 90 participants / 539 sensitivity scenarios It includes: anonymized confirmatory and sensitivity scenario-level datasets, frozen criterion weights and frozen stimulus payload export, exported statistical summaries, a reproduction script and README. This version is intended to support reproduction of reported tables, descriptive summaries, and key inferential results from the frozen export snapshot, while also documenting the shared empirical basis of the companion ISDA 2026, ICIICE 2026, and TILE-TEC 2026 publications.