{"id":"W3115448160","doi":"10.3310/hta24720","title":"Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis","year":2020,"lang":"en","type":"article","venue":"Health Technology Assessment","topic":"Pregnancy and preeclampsia studies","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Montréal; University of Toronto; Centre Hospitalier Universitaire Sainte-Justine; Mount Sinai Hospital","funders":"National Institutes of Health; Tommy's; Sigrid Juséliuksen Säätiö; Signe ja Ane Gyllenbergin Säätiö; National Institute for Health and Care Research; Novo Nordisk; National Health and Medical Research Council; Novo Nordisk Fonden; Academy of Finland; King's Health Partners; Health Technology Assessment Programme; European Commission; Medical Research Council; Yrjö Jahnssonin Säätiö; University of Southampton; Foundation for Cardiovascular Research; Roche; Juho Vainion Säätiö; GlaxoSmithKline","keywords":"Eclampsia; Medicine; Meta-analysis; Obstetrics; Internal medicine; Pregnancy","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":["metaresearch","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.1171973,0.004602023,0.01459409,0.006445891,0.0006744559,0.004034696,0.00558001,0.00340478,0.003290162],"category_scores_gemma":[0.1465372,0.002261287,0.06910486,0.004303242,0.001014213,0.002595992,0.00284352,0.004238875,0.0005742235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002184206,"about_ca_system_score_gemma":0.003201164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006866603,"about_ca_topic_score_gemma":0.005783059,"domain_scores_codex":[0.9306327,0.05873943,0.003923462,0.004323434,0.001814056,0.0005667904],"domain_scores_gemma":[0.8465107,0.1373539,0.005744651,0.006590996,0.003203094,0.0005967527],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.006888828,0.00009151432,0.01461693,0.03157729,0.8674068,0.000283035,0.0001218003,0.05877087,0.0003790988,0.0008497194,0.001793541,0.0172206],"study_design_scores_gemma":[0.002730963,0.0008731184,0.005100972,0.003038124,0.9307941,0.0002506384,0.00005320505,0.04791622,0.0005096016,0.005335119,0.003273037,0.0001248717],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1156412,0.5921284,0.2566222,0.005944541,0.002468592,0.005520269,0.01647577,0.002040341,0.003158656],"genre_scores_gemma":[0.8625945,0.0411567,0.0790178,0.002185004,0.0004688556,0.007044774,0.005822337,0.0004322989,0.001277613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9854059,"threshold_uncertainty_score":0.6198061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5534353641377758,"score_gpt":0.5031920126653394,"score_spread":0.05024335147243641,"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."}}