{"id":"W2610508316","doi":"10.25011/cim.v40i2.28200","title":"Training the next generation of Canadian Clinician-Scientists: charting a path to success","year":2017,"lang":"en","type":"article","venue":"Clinical and investigative medicine","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; McGill University; University of Toronto; University of Manitoba; Western University","funders":"","keywords":"Mentorship; Medical education; Acknowledgement; Financial compensation; Career path; Training (meteorology); Medicine; Economic shortage; Best practice; Workforce; Career development; Compensation (psychology); Psychology; Political science; Government (linguistics); Management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0494164,0.001373201,0.001309733,0.004914375,0.02938288,0.02230101,0.005840207,0.008050678,0.01827049],"category_scores_gemma":[0.09615596,0.001056561,0.001303751,0.007056588,0.009150425,0.01205916,0.01595335,0.01571787,0.003927833],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1148509,"about_ca_system_score_gemma":0.6788737,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9297652,"about_ca_topic_score_gemma":0.9669827,"domain_scores_codex":[0.9534367,0.009351297,0.001789344,0.002071139,0.01863059,0.01472099],"domain_scores_gemma":[0.7103603,0.01585717,0.005690054,0.003543164,0.09462585,0.1699233],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001944683,0.0002349718,0.02418196,0.002263715,0.00009030773,0.000726137,0.01491366,0.0006777885,0.0005486383,0.03434705,0.7296681,0.1921533],"study_design_scores_gemma":[0.0001318803,0.0002378426,0.03546142,0.00504648,0.0001440114,0.0004797515,0.0531011,0.001642576,0.0007270026,0.01709574,0.885565,0.0003670711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01219263,0.01284607,0.002983487,0.9356083,0.006115381,0.000341585,0.0007902408,0.0003979432,0.02872436],"genre_scores_gemma":[0.5079275,0.06755736,0.09509027,0.2764766,0.003852201,0.001217212,0.003608349,0.0009385771,0.0433319],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9505836,"threshold_uncertainty_score":0.8333058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8412550295308091,"score_gpt":0.5445980411531559,"score_spread":0.2966569883776532,"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."}}