{"id":"W2605865302","doi":"10.1136/bmjstel-2016-000185","title":"Residents’ use of mobile technologies: three challenges for graduate medical education","year":2017,"lang":"en","type":"article","venue":"BMJ Simulation & Technology Enhanced Learning","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Royal College of Physicians and Surgeons of Canada","keywords":"Ambiguity; Context (archaeology); Variety (cybernetics); Reflexivity; Mobile technology; Medical education; Mobile device; Psychology; Knowledge management; Medicine; Engineering ethics; Sociology; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.01143174,0.0003386975,0.0003558857,0.0007486898,0.006391294,0.005670046,0.001159988,0.002926888,0.002486316],"category_scores_gemma":[0.02824508,0.0004589166,0.0004013033,0.0009654242,0.004797011,0.005295157,0.005624331,0.003200374,0.0005226476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002253414,"about_ca_system_score_gemma":0.006787775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002825428,"about_ca_topic_score_gemma":0.005959015,"domain_scores_codex":[0.9921812,0.004231699,0.0004528225,0.0004384102,0.001678257,0.001017669],"domain_scores_gemma":[0.9775865,0.01344113,0.002507881,0.000777879,0.002883845,0.002802789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001200482,0.0002796056,0.08440764,0.000991607,0.00003728056,0.00489958,0.7237207,0.0003164255,0.003283588,0.005420505,0.008863566,0.1676594],"study_design_scores_gemma":[0.00001320522,0.000355437,0.03248384,0.0006160106,0.00002652532,0.003650228,0.92118,0.0003807399,0.001012083,0.00323076,0.03698337,0.00006797136],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9299946,0.002164788,0.005241454,0.05403456,0.0002093997,0.0001641485,0.00008899901,0.00005807282,0.008043926],"genre_scores_gemma":[0.9909157,0.001290921,0.003903836,0.002583541,0.00007680707,0.0001219361,0.00002932115,0.000009996855,0.001067995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01143174,"threshold_uncertainty_score":0.06045753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1999219148509848,"score_gpt":0.52470383741408,"score_spread":0.3247819225630951,"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."}}