{"id":"W2081543083","doi":"10.1542/peds.2008-0377","title":"Using a Count of Neonatal Morbidities to Predict Poor Outcome in Extremely Low Birth Weight Infants: Added Role of Neonatal Infection","year":2008,"lang":"en","type":"article","venue":"PEDIATRICS","topic":"Neonatal and Maternal Infections","field":"Medicine","cited_by":277,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Glenrose Rehabilitation Hospital; University of Toronto; McMaster University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Center for Research Resources","keywords":"Medicine; Necrotizing enterocolitis; Retinopathy of prematurity; Bronchopulmonary dysplasia; Pediatrics; Enterocolitis; Meningitis; Neonatal infection; Odds ratio; Intraventricular hemorrhage; Birth weight; Low birth weight; Neonatal sepsis; Sepsis; Gestational age; Internal medicine; Pregnancy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001481303,0.0001863505,0.0004244827,0.0006441709,0.00005631689,0.000005650883,0.00007996881,0.0001146196,0.0001533891],"category_scores_gemma":[0.0001960206,0.0001715231,0.0001258536,0.0007199164,0.00008208054,0.0002215248,0.00009236908,0.000217532,0.00001746899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008971037,"about_ca_system_score_gemma":0.0001915467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004675426,"about_ca_topic_score_gemma":0.0001858216,"domain_scores_codex":[0.998416,0.00002782532,0.0006246673,0.0002214082,0.0004487796,0.0002612922],"domain_scores_gemma":[0.9991488,0.00007745924,0.0002073255,0.0002026241,0.0002188655,0.0001449637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003361302,0.0002363979,0.9899229,0.0004328378,0.00002868738,0.00007371682,0.0009120876,0.0003641604,0.004825864,0.00008446056,0.0002503563,0.002532447],"study_design_scores_gemma":[0.005742325,0.001261199,0.9343094,0.0003256249,0.0003076668,0.001102658,0.0005233454,0.003475017,0.0334245,0.00030667,0.0185395,0.0006821058],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962465,0.0008956173,0.001390559,0.00004031746,0.0004335912,0.0003609283,0.0003293071,0.00005570624,0.0002475311],"genre_scores_gemma":[0.9971932,0.0005488975,0.001465272,0.00007908692,0.0003922464,0.00001744047,0.00003846428,0.00002744943,0.0002379239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05561346,"threshold_uncertainty_score":0.7067877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02914171621275117,"score_gpt":0.2764053703344694,"score_spread":0.2472636541217183,"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."}}