{"id":"W2997157194","doi":"10.1002/jgc4.1203","title":"Genetic counselors with advanced skills: I. Refining a model of advanced training","year":2019,"lang":"en","type":"article","venue":"Journal of Genetic Counseling","topic":"Counseling Practices and Supervision","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's Health Research Institute; BC Mental Health & Substance Use Services","funders":"National Institutes of Health","keywords":"Genetic counseling; Medical education; Nonprobability sampling; Psychology; Training (meteorology); Genetic testing; Medicine; Population; Genetics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001117122,0.0003255344,0.0007749879,0.0003132413,0.00009731663,0.00004693217,0.00045754,0.0001596419,0.0003720042],"category_scores_gemma":[0.0000935419,0.0002724222,0.000217374,0.0003606236,0.00006892008,0.0002705904,0.00002236365,0.0005722395,0.00003230912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004828306,"about_ca_system_score_gemma":0.0003820832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001844509,"about_ca_topic_score_gemma":0.00001881977,"domain_scores_codex":[0.9966397,0.0001353149,0.001379411,0.000411129,0.0009171951,0.0005173079],"domain_scores_gemma":[0.9964925,0.0005088401,0.001414724,0.0005532793,0.0008527528,0.000177887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001491662,0.0002258128,0.001874396,0.00008362361,0.0002541546,0.00008052086,0.03437874,0.5361916,0.02620528,0.00003703055,0.00006769603,0.3991095],"study_design_scores_gemma":[0.06551002,0.0313232,0.03650498,0.01325518,0.003685422,0.0111104,0.1555454,0.533787,0.002359174,0.003708054,0.1361403,0.007070864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672486,0.01293131,0.01743763,0.0000921894,0.0009344518,0.0001867947,0.000006178173,0.0000240388,0.001138763],"genre_scores_gemma":[0.9108855,0.003915556,0.08428968,0.000199828,0.0001432672,0.00000624261,0.000001092743,0.00007755219,0.0004812535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3920386,"threshold_uncertainty_score":0.9999728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064586925886916,"score_gpt":0.295573521667493,"score_spread":0.2749276524086238,"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."}}