{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003662854,0.0001702732,0.0003749502,0.0003568639,0.00004252254,0.00002374068,0.00008956627,0.00007690748,0.00004802678],"category_scores_gemma":[0.0002230595,0.0001325324,0.00006844375,0.0002771477,0.00002846334,0.0001033683,0.0001241495,0.0003504121,0.000006696801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000799849,"about_ca_system_score_gemma":0.00006484772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004158604,"about_ca_topic_score_gemma":0.000005304081,"domain_scores_codex":[0.998831,0.00008815481,0.0003873105,0.0002924489,0.000203312,0.0001977725],"domain_scores_gemma":[0.9995927,0.0001057509,0.00004958369,0.0001512023,0.00002658149,0.0000742298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001062866,0.00001007973,0.9842093,0.0001170617,0.00006314881,0.00002292849,0.002173698,0.00003981423,0.002244862,0.0000127563,0.0001100839,0.01089],"study_design_scores_gemma":[0.0005795967,0.0001133605,0.991344,0.001054875,0.00004342416,0.00006588912,0.00002851137,0.002635304,0.003527558,0.00002084849,0.0004478986,0.0001386971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958607,0.0004188185,0.0004176956,0.00009703315,0.0004583265,0.0004045544,0.00003829999,0.0001344255,0.002170151],"genre_scores_gemma":[0.9881133,0.00003966628,0.01105832,0.00009522869,0.00004415163,0.00001553154,0.0004301327,0.00002419184,0.0001795215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01075131,"threshold_uncertainty_score":0.5404512,"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."}}