{"id":"W2799851871","doi":"10.1503/cmaj.1041727","title":"Global IDEA","year":2005,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Global Health and Surgery","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Global health; Computer science; Data science; Global population; Developing country; Population; Medicine; Public health; Economic growth; Environmental health; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003204527,0.0007718256,0.0006902135,0.0006542706,0.00407857,0.005878429,0.0018797,0.03755277,0.05802942],"category_scores_gemma":[0.01646656,0.0002652609,0.0008403035,0.0006369529,0.003297598,0.004369713,0.002507347,0.02941461,0.02620006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005163781,"about_ca_system_score_gemma":0.006506134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006523967,"about_ca_topic_score_gemma":0.0125732,"domain_scores_codex":[0.9969805,0.0006391896,0.0001282462,0.0004840274,0.001146436,0.0006215636],"domain_scores_gemma":[0.9947302,0.001723804,0.0002943414,0.0003600542,0.001551216,0.001340412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001245044,0.000005812996,0.00009586557,0.00002182448,0.000002460115,0.0001566219,0.00005324559,0.000007232107,0.00002607545,0.009942389,0.9858144,0.003861594],"study_design_scores_gemma":[0.00001382562,0.00000956572,0.0001404433,0.00008636548,0.000004296372,0.0002595021,0.00014125,0.00002682468,0.00002656062,0.003285356,0.9959995,0.000006583376],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.0001716852,0.001916352,0.0001112539,0.933799,0.02935629,0.000009575377,0.00009979466,0.00004736949,0.03448861],"genre_scores_gemma":[0.003803872,0.0008290682,0.0001293947,0.9312994,0.01387828,0.00002371641,0.00006164312,0.00002990422,0.04994472],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.05802942,"threshold_uncertainty_score":0.1941277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00851061356890665,"score_gpt":0.2668471386756736,"score_spread":0.258336525106767,"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."}}