{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000285213,0.0003088755,0.0004591971,0.0001568485,0.0001494577,0.00007128346,0.0001547684,0.0002920937,0.0001256731],"category_scores_gemma":[0.00006067547,0.0002162505,0.0002193753,0.00006596407,0.0001224947,0.0000496527,0.0004487294,0.0008770386,0.000002212361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003761035,"about_ca_system_score_gemma":0.0001773905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007444926,"about_ca_topic_score_gemma":0.000006920057,"domain_scores_codex":[0.9983449,0.00008644267,0.0004814704,0.0005086478,0.0003134157,0.0002651517],"domain_scores_gemma":[0.9989831,0.0001442475,0.0002416809,0.0003992609,0.00009751511,0.0001341537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00267754,0.0001578468,0.5971204,0.008940483,0.001358717,0.002539784,0.003489716,0.0002458304,0.3792295,0.00002367017,0.0001469651,0.00406956],"study_design_scores_gemma":[0.007620708,0.002639191,0.6447842,0.00815706,0.004917644,0.03383318,0.0001607524,0.05837332,0.2298638,0.002062985,0.00650913,0.001078102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872053,0.009362548,0.0002897382,0.0001107553,0.0009018308,0.001031728,0.0007795044,0.0001045665,0.000214019],"genre_scores_gemma":[0.9949088,0.000576143,0.0009968125,0.00004661641,0.0006469616,0.0001099407,0.0001134893,0.00006438965,0.002536915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1493657,"threshold_uncertainty_score":0.8818437,"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."}}