{"id":"W1716963185","doi":"10.2196/mededu.4676","title":"Formation of a New Entity to Support Effective Use of Technology in Medical Education: The Student Technology Committee","year":2015,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Component (thermodynamics); Health technology; Technology education; Educational technology; Engineering ethics; Medical education; Engineering management; Knowledge management; Computer science; Engineering; Mathematics education; Political science; Psychology; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004794392,0.0001252559,0.000231055,0.0006243766,0.00001632723,0.000009053837,0.000397622,0.0003880384,0.0001414186],"category_scores_gemma":[0.001721643,0.0001001082,0.00003251224,0.001453802,0.0001413783,0.0001530873,0.0000781232,0.0003941316,0.0000269985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002331652,"about_ca_system_score_gemma":0.001949664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001232433,"about_ca_topic_score_gemma":0.00009324386,"domain_scores_codex":[0.9984639,0.00003445716,0.0004919951,0.0001427936,0.0006731508,0.0001937138],"domain_scores_gemma":[0.999015,0.00006717291,0.00007124551,0.0003176055,0.0001749704,0.0003539847],"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":[0.00002457515,0.001777342,0.01634047,0.0005216789,0.00003701855,0.000001289712,0.007056714,0.0001417488,0.0003662501,0.006695216,0.1881381,0.7788997],"study_design_scores_gemma":[0.004586543,0.00200833,0.2715785,0.004626935,0.000151316,0.0003801247,0.02262659,0.01399143,0.01817923,0.02215162,0.6382951,0.001424319],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618419,0.0003177338,0.003437938,0.03123917,0.001970487,0.0007965871,0.000001831184,0.0001406789,0.0002536665],"genre_scores_gemma":[0.9980321,0.00004111982,0.0007878835,0.0003402628,0.000189623,0.000478166,0.00003009577,0.00001437574,0.00008639947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7774753,"threshold_uncertainty_score":0.4082293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055706711071393,"score_gpt":0.31051924055883,"score_spread":0.299962173448116,"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."}}