{"id":"W4413348919","doi":"10.1088/3049-477x/adfd63","title":"Developing adjustable birth weight cutoffs based on maternal height and Apgar scores","year":2025,"lang":"en","type":"article","venue":"Machine Learning Health","topic":"Birth, Development, and Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"University of Winnipeg","keywords":"Apgar score; Obstetrics; Medicine; Birth weight; Pregnancy; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.006609483,0.0007614009,0.0005588087,0.002494879,0.0004656945,0.001347475,0.001695697,0.0006670544,0.001832046],"category_scores_gemma":[0.02873318,0.0002616689,0.0006981458,0.002124768,0.0002567579,0.0009171054,0.001373797,0.001253184,0.001094726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130277,"about_ca_system_score_gemma":0.001807147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03557963,"about_ca_topic_score_gemma":0.057253,"domain_scores_codex":[0.9970139,0.0009993245,0.0005158643,0.0005824418,0.0006878981,0.0002005865],"domain_scores_gemma":[0.9916859,0.003650331,0.001273376,0.000919336,0.002316422,0.0001547203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002974436,0.0002729954,0.6913323,0.0004740498,0.0002064515,0.0001949738,0.0003875657,0.02949142,0.00189742,0.006295194,0.03984182,0.2293083],"study_design_scores_gemma":[0.0001150062,0.0002535736,0.5986391,0.0009085069,0.0001669899,0.0004290273,0.001343217,0.2955837,0.01068214,0.01508774,0.07663781,0.0001532684],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4971604,0.002215615,0.347573,0.002742343,0.000558079,0.00162832,0.1249939,0.002725778,0.02040265],"genre_scores_gemma":[0.5598789,0.0009947532,0.2841057,0.000548723,0.0000666499,0.001653612,0.1497376,0.0002204391,0.002793616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03557963,"threshold_uncertainty_score":0.07074505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01760213452012567,"score_gpt":0.3062547764878024,"score_spread":0.2886526419676767,"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."}}