{"id":"W2015929254","doi":"10.1016/j.jclinepi.2014.11.010","title":"Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD statement","year":2015,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":303,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Albert-Ludwigs-Universität Freiburg; ZonMw; University of Oxford; National Institute for Health and Care Research; University College London; University of North Carolina at Chapel Hill; Cancer Research UK; Medical Research Council; University of Ottawa; Memorial Sloan-Kettering Cancer Center","keywords":"Tripod (photography); Checklist; Statement (logic); Medicine; Computer science; Psychology; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"reporting","study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch"],"domain":"reporting","study_design":"not_applicable","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.7836594,0.0002534072,0.01144093,0.0002372827,0.0000947537,0.00006719368,0.001617035,0.0002736652,0.0003309689],"category_scores_gemma":[0.8844853,0.00008756111,0.004805312,0.0005576016,0.0001874298,0.0002398705,0.00009649443,0.0005379159,0.00001184294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000421998,"about_ca_system_score_gemma":0.0007401074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001409105,"about_ca_topic_score_gemma":0.00002151955,"domain_scores_codex":[0.7409983,0.06323958,0.1892621,0.001060269,0.004822604,0.0006171642],"domain_scores_gemma":[0.3160237,0.3572543,0.3145018,0.002886344,0.008372199,0.0009616192],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005393419,0.0005866323,0.6808407,0.00006864983,0.001250794,0.000004424712,0.0007358858,0.04932953,0.000001726753,0.0005117758,0.2100863,0.05604429],"study_design_scores_gemma":[0.003159972,0.002650307,0.08628216,0.0002455515,0.00247868,0.00006486063,0.001232099,0.7717086,0.0000196323,0.05606253,0.07591117,0.0001844418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1970637,0.001246194,0.7806811,0.01750383,0.001588155,0.001658443,0.0001225445,0.000003765881,0.0001322233],"genre_scores_gemma":[0.8628246,0.0004275419,0.1341819,0.001150662,0.0005718453,0.0001881673,0.000007201658,0.00001411693,0.0006339781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7223791,"threshold_uncertainty_score":0.7820794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9790934224689305,"score_gpt":0.7082666694618389,"score_spread":0.2708267530070916,"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."}}