{"id":"W2414567526","doi":"","title":"Hybrid training for remotely situated general practice registrars--making best use of available opportunities.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Rural Health Research Society","funders":"","keywords":"Training (meteorology); Situated; Vocational education; Project commissioning; Government (linguistics); Best practice; General practice; Engineering; Engineering management; Publishing; Computer science; Management; Medicine; Political science; Geography; Pedagogy; Psychology; Artificial intelligence; Family medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004416026,0.0003400579,0.000162316,0.0004737576,0.002249693,0.001338306,0.001693623,0.001213605,0.01549502],"category_scores_gemma":[0.006528803,0.0002782614,0.0004372112,0.0003416836,0.0008723219,0.0018506,0.007320311,0.001000877,0.002186163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008944549,"about_ca_system_score_gemma":0.003402588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001894183,"about_ca_topic_score_gemma":0.008348733,"domain_scores_codex":[0.9971679,0.001742647,0.0000864621,0.0002012504,0.000292151,0.0005095899],"domain_scores_gemma":[0.9969482,0.0007935233,0.0003642538,0.0004017658,0.0001542961,0.001337996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006817551,0.001911219,0.05792966,0.001574465,0.00005085005,0.002782098,0.0234725,0.002528108,0.006005584,0.003377663,0.01754885,0.8821373],"study_design_scores_gemma":[0.001367918,0.02152823,0.4065496,0.005282658,0.0002776887,0.02807578,0.1541616,0.008812638,0.007691342,0.01703572,0.3488733,0.0003434003],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9010919,0.003135573,0.02356726,0.01396065,0.0006240594,0.001294612,0.000193912,0.0006906865,0.05544128],"genre_scores_gemma":[0.9537804,0.000869361,0.03447886,0.001123645,0.0001497819,0.0005091951,0.0001057365,0.00003834988,0.008944808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01549502,"threshold_uncertainty_score":0.05183607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4738768231598258,"score_gpt":0.4365376452390187,"score_spread":0.03733917792080715,"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."}}