{"id":"W4402468000","doi":"10.1101/2024.09.11.24313497","title":"Machine learning for the prediction of spontaneous preterm birth using early second and third trimester maternal blood gene expression: A Cautionary Tale","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Preterm Birth and Chorioamnionitis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Langara College; University of Calgary","funders":"","keywords":"First trimester; Obstetrics; Third trimester; Expression (computer science); Medicine; Pregnancy; Biology; Fetus; Genetics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02180218,0.001123844,0.001499217,0.001162118,0.0006585477,0.002915826,0.001873241,0.001511478,0.001301001],"category_scores_gemma":[0.0475745,0.0003648298,0.001814507,0.00125379,0.001147868,0.001575045,0.001180814,0.007740272,0.00113871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006263317,"about_ca_system_score_gemma":0.001490222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006825248,"about_ca_topic_score_gemma":0.006544084,"domain_scores_codex":[0.993535,0.004631393,0.0004384455,0.0006717783,0.0005887872,0.000134523],"domain_scores_gemma":[0.9792463,0.01521561,0.0007457261,0.002172718,0.002326838,0.0002927146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002911972,0.0006405853,0.2195735,0.002060588,0.006427996,0.001600453,0.000983001,0.1311817,0.01028074,0.01216446,0.1327379,0.4794371],"study_design_scores_gemma":[0.0003333602,0.001370788,0.06105369,0.002429498,0.001035981,0.001003535,0.0009088533,0.7918151,0.008044791,0.08577731,0.04586064,0.0003664162],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1922264,0.1042954,0.5024873,0.1739222,0.01146247,0.0004834656,0.005406697,0.00329077,0.006425276],"genre_scores_gemma":[0.7674074,0.01662263,0.1783922,0.02250503,0.006183098,0.0005317265,0.00302937,0.000487079,0.004841538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02180218,"threshold_uncertainty_score":0.1153024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0179511063379542,"score_gpt":0.2460387123021896,"score_spread":0.2280876059642354,"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."}}