{"id":"W4386715883","doi":"10.46747/cfp.6909655","title":"A better future","year":2023,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data science; Cohort; IMG; Medical education; Medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002114362,0.0001889823,0.0002516253,0.0002583378,0.00107154,0.00001166244,0.0002929738,0.0002366644,0.00006059059],"category_scores_gemma":[0.00001039989,0.0001899628,0.00007033155,0.001142833,0.00004492426,0.0001041924,0.00004583771,0.0005807377,0.02309819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005899117,"about_ca_system_score_gemma":0.00100833,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02731524,"about_ca_topic_score_gemma":0.06908436,"domain_scores_codex":[0.9974585,0.0001720474,0.0003019351,0.0003168571,0.0002085516,0.001542097],"domain_scores_gemma":[0.9983677,0.00009451053,0.00007393717,0.0004702311,0.0001064425,0.0008871998],"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":[0.000003946268,0.00000339704,0.00206889,0.00005971743,0.00001050092,0.00004632626,0.0005825428,0.000003735549,0.00006493709,0.003410361,0.964956,0.02878958],"study_design_scores_gemma":[0.0002139027,0.00001787274,0.03985865,0.0001521548,0.000006918403,5.553282e-8,0.009759034,0.0000607994,0.000002562446,0.001567996,0.948177,0.0001830776],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.2811461,0.000366509,0.000001802439,0.01962514,0.003393315,0.0007596862,0.000192797,0.0004951027,0.6940195],"genre_scores_gemma":[0.2150682,0.00008893792,0.0001078833,0.7634266,0.006512775,0.0002432796,0.0003027697,0.0001061729,0.01414335],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7438015,"threshold_uncertainty_score":0.979162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03949214562076087,"score_gpt":0.3649073223547762,"score_spread":0.3254151767340153,"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."}}