{"id":"W3193986332","doi":"10.1002/uog.23757","title":"External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (<scp>IPPIC</scp>) Network database: individual participant data meta‐analysis","year":2021,"lang":"en","type":"article","venue":"Ultrasound in Obstetrics and Gynecology","topic":"Maternal and Perinatal Health Interventions","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Health Technology Assessment Programme; Norwegian Institute of Public Health; College of Engineering, Michigan State University; Akershus Universitetssykehus; King's College London; Universitat de Barcelona; Università Cattolica del Sacro Cuore; Johns Hopkins University; Universitetet i Oslo; Université de Montréal; Rigshospitalet; Universidad de Granada; National and Kapodistrian University of Athens; Michigan State University; Universitair Medisch Centrum Groningen; Università degli Studi di Parma; Aarhus Universitet; Kementerian Pendidikan Nasional; Khon Kaen University; Università degli Studi di Milano-Bicocca; University of New South Wales; Universiteit Maastricht; Universidad de los Andes; NIHR School for Primary Care Research; Universidade de São Paulo; National Center for Child Health and Development; RMIT University; Portland State University; University of Toronto; World Health Organization; University of Dundee; University College Dublin; University of Bristol; University of Cambridge; University of North Carolina at Chapel Hill; Queen Mary University of London; National Institute for Health and Care Research; Assistance publique-Hôpitaux de Paris; Medical Research Council; Università degli Studi di Brescia; University of Aberdeen; Università degli Studi di Milano; Universidad Complutense de Madrid; Norges Teknisk-Naturvitenskapelige Universitet; South Australian Health and Medical Research Institute; University of South Florida; University of Oxford; Centre Hospitalier Universitaire de Québec; Monash University; Helsingin Yliopisto; Université Laval; Academisch Medisch Centrum; Universitätsspital Basel; Syddansk Universitet","keywords":"Medicine; Meta-analysis; Predictive modelling; Calibration; Pregnancy; Statistic; MEDLINE; Discriminative model; Cohort study; Obstetrics; Statistics; Machine learning; Internal medicine; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05874496,0.002524203,0.009297197,0.004159847,0.0004789552,0.003014611,0.002877417,0.001853935,0.003661053],"category_scores_gemma":[0.1304617,0.001076689,0.04171588,0.004901458,0.0006325916,0.00164176,0.002195186,0.002370998,0.0005720221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468429,"about_ca_system_score_gemma":0.0028495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00412212,"about_ca_topic_score_gemma":0.004993139,"domain_scores_codex":[0.9697057,0.02009495,0.004956455,0.00250854,0.0023211,0.0004131669],"domain_scores_gemma":[0.8963171,0.08373736,0.009786064,0.006168974,0.003554566,0.0004358831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.00615825,0.0000561272,0.02565897,0.1058893,0.8367509,0.0001117724,0.00008331436,0.004373755,0.0002347666,0.0004608386,0.001961998,0.01826004],"study_design_scores_gemma":[0.001990521,0.0004175162,0.01033909,0.008952235,0.9717222,0.00009697845,0.00002735682,0.002414612,0.0002539029,0.0009149711,0.002825851,0.00004485857],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06105336,0.8730919,0.02754257,0.001858053,0.0009062373,0.003331406,0.02864476,0.0004470089,0.003124595],"genre_scores_gemma":[0.8033373,0.1390506,0.02404374,0.001997156,0.0005984016,0.007909244,0.02142821,0.0003277254,0.001307722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05874496,"threshold_uncertainty_score":0.3106768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2389665380762145,"score_gpt":0.3711748934073784,"score_spread":0.1322083553311639,"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."}}