{"id":"W2031104886","doi":"10.3109/0142159x.2014.993601","title":"Sea monsters & whirlpools: Navigating between examination and reflection in medical education","year":2014,"lang":"en","type":"article","venue":"Medical Teacher","topic":"Innovations in Medical Education","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto","funders":"","keywords":"Competence (human resources); Presentation (obstetrics); Reflection (computer programming); Medical education; Psychology; Sociology; Medicine; Radiology; Computer science; Social psychology","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":[0.009586525,0.0003893018,0.0003220525,0.001009449,0.008693253,0.0114757,0.001109891,0.005001798,0.01324789],"category_scores_gemma":[0.02020619,0.0004769356,0.0004383322,0.001116166,0.01377955,0.008030212,0.008000932,0.00764815,0.001921198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003511363,"about_ca_system_score_gemma":0.008432101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01587977,"about_ca_topic_score_gemma":0.03961698,"domain_scores_codex":[0.9940035,0.003874107,0.0001869485,0.0003499182,0.001074549,0.0005109842],"domain_scores_gemma":[0.9913947,0.005331439,0.0003699262,0.0003912512,0.0008609155,0.001651724],"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":[0.00009557392,0.00005670803,0.0008832642,0.000425114,0.00001305723,0.0008680198,0.1077441,0.0001973484,0.0009091622,0.08403534,0.6320667,0.1727056],"study_design_scores_gemma":[0.00001093821,0.0000602934,0.0009771803,0.0008181256,0.000006618231,0.0004303281,0.07103053,0.0001737836,0.0006949189,0.01758067,0.9081756,0.00004102264],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01875822,0.03470276,0.009313054,0.7890731,0.028567,0.0001432045,0.00006479376,0.0003269472,0.1190509],"genre_scores_gemma":[0.4327013,0.04331966,0.01465129,0.08462433,0.009028207,0.0001811282,0.00008192914,0.0006297755,0.4147824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01587977,"threshold_uncertainty_score":0.050699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02971372575847317,"score_gpt":0.3943879235781461,"score_spread":0.3646741978196729,"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."}}