{"id":"W4405324107","doi":"10.3390/children11121512","title":"Prediction of Neurodevelopmental Outcomes in Very Preterm Infants: Comparing Machine Learning Methods to Logistic Regression","year":2024,"lang":"en","type":"article","venue":"Children","topic":"Infant Development and Preterm Care","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Medicine; Logistic regression; Gestational age; Cohort; Pediatrics; Population; Retrospective cohort study; Birth weight; Stepwise regression; Low birth weight; Pregnancy; Internal medicine","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":[0.01242256,0.0008875009,0.0009109188,0.00146318,0.0002398947,0.0009240052,0.0008892259,0.0007320337,0.0005873666],"category_scores_gemma":[0.02644784,0.0001899571,0.0008406643,0.0006112106,0.0003853525,0.0007210549,0.0008915713,0.001113943,0.0002810701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001111601,"about_ca_system_score_gemma":0.001257322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01421746,"about_ca_topic_score_gemma":0.008914311,"domain_scores_codex":[0.9965616,0.002396823,0.0001364254,0.0003674091,0.000387122,0.0001506405],"domain_scores_gemma":[0.9869539,0.00993219,0.001067759,0.000492537,0.001221537,0.0003321563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003924661,0.0004417786,0.723955,0.0003839921,0.001809482,0.0001354632,0.0001689656,0.1123628,0.0008616667,0.0006567717,0.002162376,0.153137],"study_design_scores_gemma":[0.0001938817,0.001908365,0.2191705,0.0004726477,0.0005318748,0.0003200135,0.0002518046,0.7720643,0.001497613,0.002134894,0.001390146,0.00006395145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9395109,0.008391191,0.04671702,0.001824045,0.0001806466,0.0001685711,0.0007822576,0.0003253903,0.002099948],"genre_scores_gemma":[0.9891717,0.0008583423,0.008779874,0.0001710797,0.0000663192,0.00004362583,0.0005731044,0.00002062382,0.0003154771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01421746,"threshold_uncertainty_score":0.06569755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04285299938503814,"score_gpt":0.3357866879743054,"score_spread":0.2929336885892673,"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."}}