{"id":"W4379046100","doi":"10.1016/j.ijrobp.2023.03.021","title":"Tailored Mentorship for the Underrepresented & Allies in Radiation Oncology: The ARRO Equity and Inclusion Subcommittee Mentorship Experience","year":2023,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Mentoring and Academic Development","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Mentorship; Medicine; Equity (law); Attrition; Inclusion (mineral); Medical education; Radiation oncology; Underrepresented Minority; Urology; Family medicine; Internal medicine; Psychology; Radiation therapy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004522535,0.0002269619,0.0003674818,0.0002252749,0.0005325613,0.00005594115,0.001160067,0.0003242719,0.00007701669],"category_scores_gemma":[0.001040302,0.0001550715,0.0001354343,0.000363076,0.0003128242,0.0002279217,0.001233292,0.0006389962,0.000029033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001030744,"about_ca_system_score_gemma":0.0002678545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009793864,"about_ca_topic_score_gemma":0.00005458704,"domain_scores_codex":[0.9970494,0.0007571267,0.0009398996,0.0003345044,0.0004685152,0.0004505845],"domain_scores_gemma":[0.9946612,0.00364518,0.001079878,0.0002363562,0.0002676415,0.0001098007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001258422,0.0004667948,0.2478009,0.00001336366,0.0008684431,0.0000199977,0.07100955,0.001111085,0.002756553,0.03332321,0.02710605,0.6142656],"study_design_scores_gemma":[0.006539629,0.0005518845,0.1331731,0.00005760694,0.00009856818,0.00005633371,0.003983968,0.002278857,0.0007169311,0.07813332,0.7740672,0.0003426033],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070318,0.002344467,0.01032162,0.05724468,0.01992734,0.001044888,0.0000458228,0.00009942855,0.00194],"genre_scores_gemma":[0.9941196,0.001485635,0.0002893948,0.001491991,0.00190943,0.0001971675,0.0000944932,0.0000248141,0.0003874586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7469611,"threshold_uncertainty_score":0.6323632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09967933918614902,"score_gpt":0.437674331046614,"score_spread":0.3379949918604649,"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."}}