{"id":"W2996227145","doi":"10.1002/sim.8411","title":"Multistate analysis from cross‐sectional and auxiliary samples","year":2019,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Cross-sectional study; Statistics; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006177285,0.0001674636,0.0005295817,0.0001797526,0.00004996948,0.00001611191,0.0000961739,0.0000702792,0.001128419],"category_scores_gemma":[0.002693338,0.0001368877,0.00002669283,0.0002552161,0.0002534443,0.00005366325,0.00005294202,0.000231305,0.00001062155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004613581,"about_ca_system_score_gemma":0.00002040321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006287573,"about_ca_topic_score_gemma":0.0004084035,"domain_scores_codex":[0.9983801,0.000118843,0.0005283927,0.0004031357,0.0003325187,0.0002369747],"domain_scores_gemma":[0.993559,0.005831538,0.000128944,0.0002665519,0.00009800521,0.0001159422],"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":[0.0001119244,0.000068777,0.3239649,0.0001260199,0.0002873913,0.00005570189,0.0007709841,0.0003224414,0.000432471,0.6620055,0.0005795736,0.01127431],"study_design_scores_gemma":[0.000855599,0.00005944151,0.2571451,0.00002897248,0.000132804,0.000001416187,0.00008429307,0.02417571,0.00001030607,0.717155,0.0002275464,0.0001237828],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1118023,0.0001096377,0.8855963,0.00005204394,0.0002103699,0.0001703743,0.001426452,0.00002414382,0.0006084541],"genre_scores_gemma":[0.2267425,0.00008051492,0.772223,0.0001005288,0.00008003141,0.000009743768,0.0001783504,0.000017608,0.0005677413],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1149402,"threshold_uncertainty_score":0.9997847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1057837182763845,"score_gpt":0.4667082911738786,"score_spread":0.3609245728974941,"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."}}