{"id":"W1578148372","doi":"10.1503/cmaj.109-5123","title":"Online tool helps future MDs plan their careers","year":2015,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Plan (archaeology); Medical education; Medical school; Computer science; Data science; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.001966067,0.0006997908,0.0004119679,0.002733078,0.002187846,0.002258543,0.001052275,0.001290409,0.2504819],"category_scores_gemma":[0.0131999,0.0003076677,0.000458307,0.001366364,0.0002049303,0.002601725,0.002366391,0.001315188,0.08886272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002003059,"about_ca_system_score_gemma":0.00756551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02997374,"about_ca_topic_score_gemma":0.1397654,"domain_scores_codex":[0.9991522,0.0001938431,0.00007212053,0.00005778618,0.0003044358,0.0002195228],"domain_scores_gemma":[0.9889648,0.00223332,0.0005823839,0.0005485976,0.003463157,0.00420772],"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":[0.00005894479,0.0002065148,0.003674919,0.00007304864,0.000003021479,0.0001127599,0.0004777844,0.00004910436,0.00009140969,0.0003788015,0.8426528,0.1522208],"study_design_scores_gemma":[0.00005854717,0.0000735332,0.008023606,0.0003022562,0.00001173001,0.000208036,0.002570233,0.0002922062,0.0003691214,0.00114055,0.9868956,0.00005452857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07506196,0.002125433,0.02156756,0.08112645,0.007305816,0.002554146,0.05457653,0.03584024,0.7198418],"genre_scores_gemma":[0.1420839,0.004220597,0.1195213,0.01378847,0.001904249,0.002094432,0.02484025,0.002572919,0.6889739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2504819,"threshold_uncertainty_score":0.8379455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03948198930509938,"score_gpt":0.3665777555013023,"score_spread":0.3270957661962029,"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."}}