{"id":"W2774071008","doi":"10.1007/978-981-10-5370-2_15","title":"Analysis of Chronic Disease Processes Based on Cohort and Registry Data","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Censoring (clinical trials); Inference; Computer science; Disease; Cohort; Econometrics; Statistics; Medicine; Artificial intelligence; Mathematics; Pathology","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":[0.0002922285,0.000208079,0.000645017,0.0001193354,0.00005129176,0.00004104528,0.0004901493,0.0001170927,0.001640251],"category_scores_gemma":[0.004492583,0.0001552917,0.00006013726,0.00002213056,0.0002222048,0.0000341115,0.0001666582,0.00013774,0.000003947815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002094289,"about_ca_system_score_gemma":0.0003430259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001859901,"about_ca_topic_score_gemma":0.00006800199,"domain_scores_codex":[0.9988308,0.00001565634,0.0002950928,0.0004635457,0.0002920693,0.0001028265],"domain_scores_gemma":[0.9955961,0.001473605,0.0003889809,0.002277012,0.000136725,0.0001276221],"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":[0.00006269095,0.00009424404,0.001495641,0.003797361,0.001359332,0.00003225013,0.000005000711,0.000003704333,8.139844e-7,0.9710934,0.004387017,0.01766858],"study_design_scores_gemma":[0.0004336826,0.0002416868,0.005787022,0.002180702,0.02152281,7.272089e-7,0.000002950845,0.1129222,0.00001653769,0.8322871,0.02368931,0.000915262],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001469376,0.0003204646,0.2079308,0.00008814244,0.00003885957,0.0003085305,0.003985771,0.00003342337,0.7872792],"genre_scores_gemma":[0.02318777,0.001292044,0.1981728,0.0002284651,0.0002867225,0.00003369802,0.001933609,0.0001405939,0.7747243],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1388062,"threshold_uncertainty_score":0.9992724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1764725160768058,"score_gpt":0.4134356935724406,"score_spread":0.2369631774956348,"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."}}