{"id":"W3088994275","doi":"10.18260/1-2--34302","title":"Collecting and Selecting: A Tale of Training and Mentorship","year":2020,"lang":"en","type":"article","venue":"2020 ASEE Virtual Annual Conference Content Access Proceedings","topic":"Human Resource and Talent Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mentorship; Training (meteorology); Computer science; Medical education; Medicine; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.06005063,0.001373973,0.001223201,0.003573247,0.01667423,0.02603878,0.005497647,0.006642506,0.01088415],"category_scores_gemma":[0.09201875,0.0008542137,0.001272536,0.002371078,0.01998472,0.01694784,0.02340615,0.01636234,0.006736629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006460352,"about_ca_system_score_gemma":0.02260672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002725567,"about_ca_topic_score_gemma":0.004532234,"domain_scores_codex":[0.9329942,0.04270897,0.002282294,0.003551165,0.01182054,0.006642845],"domain_scores_gemma":[0.854142,0.03942569,0.004836706,0.01505898,0.02119392,0.06534272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001473106,0.0006737487,0.0039013,0.0003419561,0.00006522109,0.0008831413,0.09865656,0.0008376407,0.001548309,0.06553879,0.43858,0.3888261],"study_design_scores_gemma":[0.0000288618,0.0003390216,0.001779981,0.000847921,0.00002639964,0.0006949321,0.06074497,0.001023315,0.0009563067,0.04405909,0.8893691,0.0001301556],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02434404,0.01747908,0.07973168,0.7197977,0.02597093,0.0006067916,0.0001556702,0.002478702,0.1294354],"genre_scores_gemma":[0.395513,0.02426871,0.1328174,0.1411951,0.02584744,0.001232165,0.0004694978,0.002988694,0.2756678],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06005063,"threshold_uncertainty_score":0.3175818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1147560515922677,"score_gpt":0.2664536896041116,"score_spread":0.1516976380118439,"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."}}