{"id":"W2297949645","doi":"10.2196/mededu.5159","title":"Feasibility of Augmented Reality in Clinical Simulations: Using Google Glass With Manikins","year":2016,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Augmented reality; Fidelity; Computer science; Human–computer interaction; Multimedia","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001039987,0.0001363081,0.0003544514,0.000201719,0.00004756447,0.000005201405,0.0001057425,0.0002555613,0.00106111],"category_scores_gemma":[0.002320861,0.00009360164,0.00006739209,0.000559961,0.0002561398,0.0001380065,0.0000202075,0.0002492983,0.00001122638],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007260332,"about_ca_system_score_gemma":0.006856459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006092164,"about_ca_topic_score_gemma":0.0001654933,"domain_scores_codex":[0.9972011,0.0003211852,0.001110729,0.0004064322,0.0007339677,0.0002265477],"domain_scores_gemma":[0.9970125,0.0009097045,0.0003427098,0.0006082501,0.0006919358,0.0004348934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003564354,0.00192719,0.9846954,0.0001822421,0.00001350823,0.000001308248,0.0004350861,0.00001918307,0.0000797441,0.0003174885,0.0003207397,0.01165168],"study_design_scores_gemma":[0.002510636,0.0001820512,0.9916123,0.001177285,0.0000302746,0.00001436277,0.0005994863,0.002976749,0.00006183625,0.0003997778,0.0003317417,0.0001035403],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840373,0.00004754234,0.0007315908,0.01319235,0.0005146263,0.001221492,0.0000123918,0.00004302867,0.0001996219],"genre_scores_gemma":[0.9973397,0.00001084084,0.001109813,0.0008662941,0.0003921762,0.00006866992,0.00008135581,0.00002014633,0.0001110501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0133023,"threshold_uncertainty_score":0.9998521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1302730885015105,"score_gpt":0.516659139832898,"score_spread":0.3863860513313875,"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."}}