{"id":"W4414476131","doi":"10.1002/psp4.70115","title":"An Open‐Source Framework for Virtual Bioequivalence Modeling and Clinical Trial Design","year":2025,"lang":"en","type":"article","venue":"CPT Pharmacometrics & Systems Pharmacology","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Waterloo","funders":"Food and Drug Administration; U.S. Food and Drug Administration; U.S. Department of Health and Human Services","keywords":"Bioequivalence; Physiologically based pharmacokinetic modelling; In silico; IVIVC; Toolbox; Rework; Inference; In vivo; Benchmark (surveying); Repurposing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.02712044,0.0005764251,0.002322923,0.0009677821,0.0004450683,0.0004280152,0.00229975,0.0008425883,0.0001589461],"category_scores_gemma":[0.0862099,0.000544262,0.0002579092,0.002287112,0.0004300103,0.0003318771,0.0008558065,0.001292904,0.00001531167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001828836,"about_ca_system_score_gemma":0.0003926244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003161509,"about_ca_topic_score_gemma":2.44596e-7,"domain_scores_codex":[0.9860591,0.007285653,0.003604239,0.001559837,0.0005141166,0.0009770242],"domain_scores_gemma":[0.8015785,0.1955983,0.0008927014,0.0007132069,0.0005832523,0.0006340679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.1273764,0.007847829,0.0003472722,0.001853501,0.003572741,0.00006846635,0.0002004402,0.006655118,0.005058579,0.6539654,0.04518026,0.147874],"study_design_scores_gemma":[0.07448085,0.004461715,0.000005531042,0.0001790574,0.002205645,0.000009285484,0.0001376214,0.4636147,0.001064769,0.4503835,0.002731973,0.0007253733],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04676314,0.0006305427,0.9211864,0.0003431707,0.02262875,0.007926081,0.0001597977,0.0002757694,0.00008630741],"genre_scores_gemma":[0.3365805,0.0006352081,0.6571993,0.001438452,0.002561051,0.001171501,0.00000465683,0.0001116462,0.0002976601],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4569596,"threshold_uncertainty_score":0.9997009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7654397942060153,"score_gpt":0.6792413634340045,"score_spread":0.08619843077201073,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}