{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007496253,0.0001748565,0.0003621397,0.0002103633,0.00006417905,0.00003374277,0.00008663128,0.00007777377,0.001127908],"category_scores_gemma":[0.005610524,0.0001416679,0.00001018375,0.0001566158,0.000289143,0.00006331524,0.00004468645,0.0003135421,0.00001484975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004378259,"about_ca_system_score_gemma":0.0000479955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003520786,"about_ca_topic_score_gemma":0.0001696015,"domain_scores_codex":[0.9983802,0.0002145678,0.0005291087,0.0003536078,0.0002687653,0.0002537011],"domain_scores_gemma":[0.9880981,0.01147876,0.00004597849,0.0001855449,0.00006638306,0.000125262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006607305,0.00002696292,0.00002303338,0.0002776107,0.00001730773,0.00006207442,0.0006977325,8.012121e-7,0.00002210815,0.7473497,0.006873187,0.2446429],"study_design_scores_gemma":[0.0003016373,0.0001192811,0.001491187,0.0004827238,0.00007023183,0.00001796826,0.0002875269,0.03351584,0.00000498823,0.959615,0.003944062,0.000149545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001415168,0.001976562,0.990319,0.003486349,0.0004948472,0.0001923462,0.0009280417,0.00007819738,0.002383211],"genre_scores_gemma":[0.09137991,0.002240118,0.9059001,0.00007757619,0.0001559993,0.00001882987,0.00008602785,0.00002950637,0.0001119287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2444933,"threshold_uncertainty_score":0.9997852,"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."}}