{"id":"W2095395446","doi":"10.1007/s12561-013-9087-8","title":"Statistical Issues in Modeling Chronic Disease in Cohort Studies","year":2013,"lang":"en","type":"article","venue":"Statistics in Biosciences","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Biostatistics; Econometrics; Disease; Cohort; Medicine; Observational study; Cohort study; Markov model; Statistics; Computer science; Markov chain; Epidemiology; Machine learning; Mathematics; Internal medicine","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"],"consensus_categories":[],"category_scores_codex":[0.001194245,0.0002120303,0.00046638,0.0002723119,0.00006430072,0.00008650825,0.0003111275,0.00005398202,0.0002847869],"category_scores_gemma":[0.01157918,0.0001728606,0.00001569347,0.0005619731,0.0005705081,0.0001656981,0.0001246239,0.0002597796,0.00003442197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002282615,"about_ca_system_score_gemma":0.0001922554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001414046,"about_ca_topic_score_gemma":0.002160665,"domain_scores_codex":[0.9974231,0.0002600862,0.0007542912,0.0005064745,0.0004810793,0.0005749445],"domain_scores_gemma":[0.9964285,0.002986191,0.00008148566,0.0002365741,0.0001164338,0.0001508255],"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":[0.00001027552,0.0001707056,0.1370626,0.0002159577,0.00000726725,0.00007550701,0.0007046969,0.000491156,0.00004124815,0.8522366,0.0005663757,0.008417616],"study_design_scores_gemma":[0.0001665004,0.00005487174,0.06359433,0.0001510892,0.000006508341,3.575982e-7,0.0004698595,0.2852312,0.000006990837,0.6501409,0.000009461048,0.0001679194],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4491345,0.001460223,0.5460121,0.000608045,0.0005301727,0.00108028,0.000451163,0.00004988597,0.0006736129],"genre_scores_gemma":[0.5998736,0.0005894502,0.3992971,0.00003919307,0.00002698781,0.0001094282,0.00000430506,0.000009526492,0.00005037151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2847401,"threshold_uncertainty_score":0.9967467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1491457927264104,"score_gpt":0.4677666348627622,"score_spread":0.3186208421363517,"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."}}