{"id":"W4392045356","doi":"10.1111/ppe.13057","title":"Pregnancy, stroke and selection bias","year":2024,"lang":"en","type":"letter","venue":"Paediatric and Perinatal Epidemiology","topic":"Pregnancy and preeclampsia studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec; Université de Montréal","funders":"","keywords":"Medicine; Pregnancy; Selection bias; Selection (genetic algorithm); Stroke (engine); Obstetrics; Artificial intelligence; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005165738,0.000433979,0.001183659,0.0002713582,0.0001408055,0.00001332186,0.00007040756,0.00121181,0.0001022496],"category_scores_gemma":[0.001194741,0.0003357867,0.0001839249,0.0001642142,0.0003027471,0.00005407636,0.0002276854,0.002252694,0.00007000726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004211552,"about_ca_system_score_gemma":0.00007947113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001046875,"about_ca_topic_score_gemma":0.000008479202,"domain_scores_codex":[0.9976647,0.0003486613,0.0005102784,0.0007995061,0.0001172449,0.0005595773],"domain_scores_gemma":[0.9971969,0.002314155,0.0001624066,0.0001692788,0.0000444948,0.0001128029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000447341,0.000007563939,0.09248443,0.004343684,0.0003340583,0.000490292,0.0001334509,2.365958e-7,0.000002585886,0.0003120812,0.8755782,0.02626863],"study_design_scores_gemma":[0.0004420531,0.0005158759,0.0229799,0.0005661863,0.0006147509,0.001569987,0.00001325999,0.0001524719,0.000002765007,0.001825585,0.9709798,0.0003374045],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004193033,0.4690552,0.0001281431,0.5178555,0.0008974337,0.0005401181,0.0002286754,0.0002044877,0.006897394],"genre_scores_gemma":[0.04710642,0.1616885,0.003055904,0.6958405,0.01735509,0.000485985,0.000493554,0.0002104908,0.07376356],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3073667,"threshold_uncertainty_score":0.9999094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06298268685043092,"score_gpt":0.3120442624058307,"score_spread":0.2490615755553998,"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."}}