{"id":"W7018433016","doi":"","title":"From diagnosis to discernment: fostering clinical judgement in high fidelity simulations","year":2012,"lang":"en","type":"other","venue":"Arca (British Columbia Electronic Library Network)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clinical judgement; Competence (human resources); Fidelity; Clinical Practice; Context (archaeology); Clinical judgment","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006249204,0.0007517115,0.001693179,0.0002020831,0.0002349824,0.00137962,0.001438896,0.0008968581,0.5709295],"category_scores_gemma":[0.0000900645,0.001454915,0.0004533544,0.001424845,0.0001611234,0.001001351,0.00232887,0.001732814,0.002117927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008285378,"about_ca_system_score_gemma":0.0004805434,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05217571,"about_ca_topic_score_gemma":0.5719973,"domain_scores_codex":[0.990486,0.001094354,0.001967857,0.002126014,0.000915789,0.003409982],"domain_scores_gemma":[0.9959375,0.0007950383,0.0007375746,0.001676617,0.00002362903,0.0008296255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005197722,0.000841041,0.1398379,0.00003476752,0.0004377557,0.00006219954,0.0000286609,0.0006279302,1.578589e-7,0.001041022,0.8121611,0.04487543],"study_design_scores_gemma":[0.00194782,0.0002695867,0.01795623,0.001858135,0.0002362689,0.000005266906,0.00000914586,0.0003115615,8.812107e-7,0.08274639,0.8931555,0.001503226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01815422,0.02840171,0.00003027091,0.0009293361,0.004981042,0.009405495,0.01046749,0.003856118,0.9237743],"genre_scores_gemma":[0.8206451,0.002737836,0.001438235,0.001404149,0.008991183,0.001307326,0.004589332,0.003154373,0.1557325],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8024908,"threshold_uncertainty_score":0.999657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01967210215567958,"score_gpt":0.2630274435162519,"score_spread":0.2433553413605723,"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."}}