{"id":"W2903570098","doi":"10.1016/j.jped.2018.10.011","title":"Prevalence, mortality and risk factors associated with very low birth weight preterm infants: an analysis of 33 years","year":2018,"lang":"en","type":"article","venue":"Jornal de Pediatria","topic":"Maternal and Neonatal Healthcare","field":"Health Professions","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Medicine; Low birth weight; Birth weight; Anthropometry; Pediatrics; Demography; Neonatal mortality; Risk factor; Infant mortality; Birth order; Obstetrics; Pregnancy; Population; Environmental health; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000674999,0.0002275885,0.0003405033,0.001709544,0.0004584248,0.0003756092,0.0003145186,0.0003186262,0.0008858065],"category_scores_gemma":[0.001276662,0.0003500374,0.000662867,0.001692631,0.0001528891,0.0004851822,0.0006069989,0.0003875075,0.000193073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004507201,"about_ca_system_score_gemma":0.00042414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01730864,"about_ca_topic_score_gemma":0.01899666,"domain_scores_codex":[0.9995777,0.00007940627,0.00006573155,0.00009356246,0.00009435494,0.00008912634],"domain_scores_gemma":[0.9991863,0.00007941038,0.0004493609,0.00004131111,0.00009542514,0.0001481596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002422655,0.00001164197,0.999166,0.000009654595,0.00003166015,0.00006689434,0.00008571867,0.00001636342,0.00006733713,0.000004883471,0.00003432799,0.0004812464],"study_design_scores_gemma":[5.318446e-7,0.00002520968,0.9996741,0.000004244497,0.000007531113,0.00008070553,0.0000994794,0.0000330296,0.00001061885,0.000002402758,0.00006076816,0.000001347613],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998585,0.0004745227,0.00006445528,0.0000165367,0.000002409378,0.000009130725,0.0007114757,0.000001786885,0.0001347077],"genre_scores_gemma":[0.9984187,0.0004279723,0.00008297594,0.00001507504,0.000005558506,0.00002713837,0.0008795083,0.000001327816,0.0001416628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01730864,"threshold_uncertainty_score":0.03441578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04107623055206288,"score_gpt":0.3739188309359343,"score_spread":0.3328426003838714,"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."}}