{"id":"W4381598380","doi":"10.1177/0272989x231178317","title":"Value-of-Information Analysis for External Validation of Risk Prediction Models","year":2023,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Cancer Institute; Canadian Institutes of Health Research; National Institutes of Health; Memorial Sloan-Kettering Cancer Center","keywords":"False positive paradox; Population; Computation; Value of information; Econometrics; Computer science; Medicine; Algorithm; Mathematics; Machine learning; Artificial intelligence","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":[0.1575073,0.002701408,0.003016681,0.00740668,0.001300642,0.003744125,0.003578884,0.002910833,0.002494197],"category_scores_gemma":[0.4464331,0.001221469,0.003801858,0.004013959,0.005143301,0.003913305,0.004189755,0.005641882,0.0003926222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003680379,"about_ca_system_score_gemma":0.004173085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002780888,"about_ca_topic_score_gemma":0.001480992,"domain_scores_codex":[0.8955767,0.08459447,0.003498146,0.004081181,0.01150568,0.0007438478],"domain_scores_gemma":[0.3434967,0.6057143,0.01790951,0.02171366,0.01008681,0.001079136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001083626,0.0004126283,0.06455357,0.001823477,0.003774134,0.0006297757,0.0008177322,0.6129274,0.001753914,0.1387819,0.004142882,0.1692988],"study_design_scores_gemma":[0.00006609916,0.000349802,0.004205186,0.0003562925,0.0001752712,0.0001259406,0.00006816662,0.9107735,0.001469815,0.08084944,0.001487891,0.00007267442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02365744,0.0011974,0.9712894,0.0005207025,0.00008557663,0.0004144489,0.0003553784,0.0004389409,0.002040664],"genre_scores_gemma":[0.6051905,0.0006895598,0.3901877,0.0004154511,0.0002001146,0.001545413,0.001011054,0.0002853246,0.0004749324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1575073,"threshold_uncertainty_score":0.8329881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2832958129662357,"score_gpt":0.4518197556432132,"score_spread":0.1685239426769775,"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."}}