{"id":"W4391841493","doi":"10.1002/sim.10012","title":"Statistical plasmode simulations–Potentials, challenges and recommendations","year":2024,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Variety (cybernetics); Key (lock); Statistical model; Set (abstract data type); Parametric statistics; Data science; Data set; Data mining; Machine learning; Theoretical computer science; Artificial intelligence; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02715797,0.001336861,0.001601207,0.002471907,0.000925959,0.004600569,0.0055283,0.004484106,0.01172921],"category_scores_gemma":[0.1449638,0.0007612914,0.001341959,0.00221763,0.002815344,0.01105032,0.003697834,0.00717927,0.005987776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001633886,"about_ca_system_score_gemma":0.004895337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005640857,"about_ca_topic_score_gemma":0.005302201,"domain_scores_codex":[0.9904355,0.006640682,0.0004910678,0.0006853323,0.001520151,0.0002273906],"domain_scores_gemma":[0.8819689,0.09098778,0.001625069,0.00743971,0.01505715,0.002921448],"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":[0.0001950292,0.0002702937,0.003903078,0.002560198,0.0001846641,0.0004119314,0.0003785297,0.07856375,0.0005856191,0.3991537,0.1487325,0.3650607],"study_design_scores_gemma":[0.00009112497,0.00006909341,0.0005144507,0.002788937,0.00004694699,0.0002222508,0.0003653292,0.1183581,0.000782723,0.7074373,0.1691694,0.0001543454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006107831,0.08544374,0.6096578,0.2691873,0.007115843,0.0003147531,0.001678118,0.005834585,0.01466009],"genre_scores_gemma":[0.0933444,0.1597285,0.7041458,0.02132577,0.007152439,0.0012891,0.002826434,0.00197555,0.008211926],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02715797,"threshold_uncertainty_score":0.1436268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1146846970201318,"score_gpt":0.4497689482758238,"score_spread":0.3350842512556919,"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."}}