{"id":"W2031614723","doi":"10.1016/j.preghy.2012.04.165","title":"PP054. Predicting preeclampsia at late mid-term pregnancy before occurrence of clinical symptoms: Clinical utility of biomarkers and clinical parameters in a low-risk population","year":2012,"lang":"en","type":"article","venue":"Pregnancy Hypertension","topic":"Pregnancy and preeclampsia studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"","keywords":"Medicine; Preeclampsia; Pregnancy; Obstetrics; Placental growth factor; Body mass index; Prospective cohort study; Gestational age; Population; Logistic regression; Cohort; Internal medicine; Environmental health","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":[0.001261334,0.0005360967,0.0003882115,0.0007465172,0.0004027021,0.0009229893,0.0004536415,0.0007700903,0.002424328],"category_scores_gemma":[0.00335951,0.0003143555,0.000553035,0.000998489,0.000240466,0.0006061297,0.0003995058,0.0008917456,0.0007179118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002890685,"about_ca_system_score_gemma":0.0005457022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002045078,"about_ca_topic_score_gemma":0.001691401,"domain_scores_codex":[0.9995427,0.0002471816,0.00003775947,0.0000621173,0.0000676574,0.00004258817],"domain_scores_gemma":[0.9987569,0.0003622961,0.0003147309,0.00006829284,0.0001910287,0.0003068212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004669927,0.0004866215,0.9804139,0.00008058112,0.0003514501,0.0001784058,0.00008095493,0.0001072264,0.001004815,0.00006897729,0.0007920291,0.01176511],"study_design_scores_gemma":[0.0002754552,0.001633733,0.9957735,0.00001819956,0.0002457686,0.0003072485,0.00008880476,0.0003287834,0.0003171183,0.0001437254,0.0008562493,0.00001146184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924574,0.001580357,0.0004711591,0.0004178698,0.0001113412,0.0001029119,0.001787552,0.00001788466,0.003053564],"genre_scores_gemma":[0.9949266,0.0004603416,0.0009254897,0.0001897067,0.0001263998,0.000132752,0.001487688,0.000005485957,0.001745658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002424328,"threshold_uncertainty_score":0.008110166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07705712109649966,"score_gpt":0.3607349070682228,"score_spread":0.2836777859717232,"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."}}