{"id":"W2404753452","doi":"10.1111/1471-0528.14029","title":"The performance of risk prediction models for pre‐eclampsia using routinely collected maternal characteristics and comparison with models that include specialised tests and with clinical guideline decision rules: a systematic review","year":2016,"lang":"en","type":"review","venue":"BJOG An International Journal of Obstetrics & Gynaecology","topic":"Pregnancy and preeclampsia studies","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"University of Notre Dame","keywords":"Eclampsia; Medicine; Guideline; Predictive modelling; Population; Aspirin; Risk assessment; False positive paradox; MEDLINE; Pregnancy; Machine learning; Computer science; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0268267,0.002340595,0.01180504,0.009519409,0.0004556331,0.003166664,0.003803077,0.00249761,0.002269581],"category_scores_gemma":[0.1145881,0.001592929,0.02160142,0.007824761,0.0008065327,0.003290431,0.001210307,0.001564252,0.0002944233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004131185,"about_ca_system_score_gemma":0.007204482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009163598,"about_ca_topic_score_gemma":0.0148192,"domain_scores_codex":[0.9814498,0.008132756,0.006008159,0.001466632,0.002721689,0.0002208258],"domain_scores_gemma":[0.8555698,0.1248536,0.0131181,0.00172786,0.004408045,0.0003225681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0009533605,0.00005759833,0.008610454,0.8566869,0.07411835,0.0001095056,0.0002003758,0.001556236,0.00008489376,0.0003477525,0.001004065,0.05627048],"study_design_scores_gemma":[0.001180964,0.0007884266,0.01448018,0.5867369,0.383481,0.0004122758,0.0002772861,0.003519385,0.0003184125,0.0009776475,0.007687176,0.0001403757],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005929358,0.990396,0.001260116,0.0003165832,0.0001055879,0.000752662,0.0008878151,0.00003534788,0.0003164468],"genre_scores_gemma":[0.1329415,0.8572089,0.005846372,0.0005158119,0.0001579407,0.001843414,0.001312632,0.00002953469,0.0001437316],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0268267,"threshold_uncertainty_score":0.1418748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09270190964192966,"score_gpt":0.3946322405998576,"score_spread":0.301930330957928,"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."}}