{"id":"W2560016122","doi":"10.1503/cmaj.1150130","title":"Maternal morbidity and perinatal outcomes in rural versus urban areas","year":2016,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Maternal and fetal healthcare","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Data science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0007956601,0.0001187717,0.0002948078,0.0007711257,0.0007762124,0.0006451734,0.0003515388,0.001491643,0.002877247],"category_scores_gemma":[0.007425993,0.0001126821,0.000198005,0.001295646,0.0005086358,0.0005343928,0.0005128354,0.001680051,0.0004721288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001332531,"about_ca_system_score_gemma":0.0007257468,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02536018,"about_ca_topic_score_gemma":0.06135629,"domain_scores_codex":[0.9991626,0.0003200993,0.00007739336,0.00009697624,0.0002095628,0.0001334474],"domain_scores_gemma":[0.9978131,0.001040713,0.0004265357,0.00005127472,0.0002657535,0.0004025433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004893774,0.0001266471,0.8204849,0.0002065633,0.00008949478,0.005618463,0.001397482,0.0001690662,0.0002774986,0.002148349,0.1187084,0.05028362],"study_design_scores_gemma":[0.00008311529,0.00029338,0.9407938,0.001057373,0.0000897518,0.01278996,0.005985714,0.0005688111,0.0002185419,0.00379517,0.03426519,0.00005922046],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.4474633,0.03201305,0.0002224929,0.4866039,0.004181786,0.00003418061,0.001275522,0.00001994256,0.02818585],"genre_scores_gemma":[0.9252332,0.0118325,0.0002162972,0.04945591,0.010018,0.0000351527,0.0003999653,0.00001736147,0.002791628],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9746398,"threshold_uncertainty_score":0.05042511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409866183650191,"score_gpt":0.2715624149207808,"score_spread":0.2574637530842789,"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."}}