{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03490131,0.0007729745,0.001430592,0.00141706,0.0007451216,0.00211615,0.00250318,0.001339796,0.003991368],"category_scores_gemma":[0.1040802,0.0007392259,0.002085936,0.001554862,0.002026536,0.002735836,0.003182907,0.003157404,0.0005680391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006600265,"about_ca_system_score_gemma":0.001148437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002042362,"about_ca_topic_score_gemma":0.002372269,"domain_scores_codex":[0.9905995,0.007147244,0.0003289978,0.001131717,0.0005992528,0.0001933637],"domain_scores_gemma":[0.888002,0.08486386,0.004845141,0.01907977,0.002558369,0.0006508057],"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":[0.000975307,0.0005122705,0.1053069,0.0007134117,0.001383103,0.0008244003,0.001850995,0.2101231,0.004286758,0.5284482,0.004399918,0.1411756],"study_design_scores_gemma":[0.00006055096,0.0002926606,0.01803028,0.0001155277,0.0002281002,0.0002457601,0.0001999992,0.7479986,0.001457493,0.2264197,0.004892078,0.00005924754],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06864174,0.0003574251,0.9287801,0.0002891675,0.00007262327,0.0001758388,0.0004646877,0.0002161248,0.001002302],"genre_scores_gemma":[0.6782538,0.0007907983,0.3123833,0.0003124552,0.0001828041,0.00109829,0.003105519,0.0001546175,0.003718486],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03490131,"threshold_uncertainty_score":0.1845779,"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."}}