{"id":"W2736292289","doi":"10.1186/s12887-017-0921-x","title":"Comparing very low birth weight versus very low gestation cohort methods for outcome analysis of high risk preterm infants","year":2017,"lang":"en","type":"article","venue":"BMC Pediatrics","topic":"Neonatal Respiratory Health Research","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Sveriges Kommuner och Landsting; Instituto Nacional de Ciência e Tecnologia em Eletrônica Orgânica; South Eastern Sydney Local Health District; Ontario Ministry of Health and Long-Term Care; Children's Hospital Foundation","keywords":"Medicine; Necrotizing enterocolitis; Gestational age; Cohort; Low birth weight; Bronchopulmonary dysplasia; Retinopathy of prematurity; Small for gestational age; Birth weight; Pediatrics; Cohort study; Population; Gestation; Obstetrics; Pregnancy; Internal medicine","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":[0.1227927,0.001309216,0.0009766091,0.00311022,0.0007449778,0.002325251,0.002780793,0.001280409,0.001751462],"category_scores_gemma":[0.1677766,0.0004347183,0.003343782,0.001332975,0.0008038156,0.001479891,0.002922516,0.002182192,0.0004079379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317531,"about_ca_system_score_gemma":0.00256581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005861797,"about_ca_topic_score_gemma":0.006003234,"domain_scores_codex":[0.9455686,0.04498829,0.002264105,0.003490395,0.003103018,0.000585605],"domain_scores_gemma":[0.8419563,0.118488,0.01328728,0.01491074,0.007894137,0.003463612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007809756,0.000359796,0.9277837,0.0003746735,0.007823509,0.0001053974,0.0003918352,0.006361423,0.0004716201,0.001562286,0.001855125,0.04510095],"study_design_scores_gemma":[0.00260698,0.01070364,0.6615521,0.001086971,0.007283848,0.001203036,0.001358751,0.2939463,0.002190974,0.01057119,0.007223599,0.0002725915],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8283682,0.007609019,0.1512707,0.001988244,0.001140158,0.002708938,0.003786241,0.0004265764,0.00270177],"genre_scores_gemma":[0.9460447,0.0007205327,0.04798435,0.0004999137,0.000271169,0.00160601,0.002168221,0.0001114464,0.0005937344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1227927,"threshold_uncertainty_score":0.6493974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1074995298697892,"score_gpt":0.4532761474304516,"score_spread":0.3457766175606624,"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."}}