{"id":"W6926358737","doi":"10.25384/sage.20210632","title":"sj-pdf-4-mdm-10.1177_0272989X221103163 – Supplemental material for An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example","year":2022,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cohort; Cohort study; Statistical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004803088,0.00146015,0.001308605,0.00195828,0.0004381354,0.002385505,0.002246103,0.00225644,0.7494805],"category_scores_gemma":[0.03442228,0.001580549,0.00197863,0.002107009,0.0004807117,0.002254752,0.001938472,0.001973534,0.4611465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283095,"about_ca_system_score_gemma":0.001680319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003314151,"about_ca_topic_score_gemma":0.005663003,"domain_scores_codex":[0.9979919,0.0008542037,0.0001798073,0.0002789198,0.0005668791,0.0001283694],"domain_scores_gemma":[0.9697751,0.02574814,0.0009086322,0.001217896,0.001824128,0.0005260899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007771434,0.0000389424,0.0003715348,0.001114137,0.00005939434,0.00007562317,0.00004001964,0.002895281,0.0004010256,0.01134195,0.9460394,0.03754494],"study_design_scores_gemma":[0.0004779875,0.00009884226,0.001684841,0.0009319998,0.00008261108,0.0003421366,0.00004195255,0.01125686,0.001909372,0.05069529,0.9323778,0.0001004116],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001368035,0.001671161,0.2747734,0.006651001,0.001426843,0.0010512,0.4263891,0.1058366,0.1808326],"genre_scores_gemma":[0.03883546,0.003955917,0.2978102,0.007868334,0.001578319,0.006674787,0.239393,0.1663365,0.2375476],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7494805,"threshold_uncertainty_score":0.3573356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06348149415039962,"score_gpt":0.3300680207738832,"score_spread":0.2665865266234836,"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."}}