{"id":"W4386139726","doi":"10.36315/2023v1end074","title":"IMMERSIVE VIRTUAL REALITY AND ARTIFICIAL INTELLIGENCE FOR ENHANCING STUDENT PREPAREDNESS FOR CLINICAL EXAMS","year":2023,"lang":"en","type":"article","venue":"Education and new developments","topic":"Innovations in Medical Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Virtual reality; Preparedness; Computer science; Human–computer interaction; Multimedia; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001012024,0.00009173727,0.0001658748,0.0001294621,0.0001633161,0.00002851137,0.00005166518,0.0000841177,0.00002180922],"category_scores_gemma":[0.001665546,0.00008889133,0.00002373376,0.0002921329,0.00006066818,0.00006859767,0.00003446937,0.0000818432,0.00001127637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010609,"about_ca_system_score_gemma":0.001314956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000125699,"about_ca_topic_score_gemma":0.00001533391,"domain_scores_codex":[0.9988337,0.00002134531,0.0005107647,0.0003072922,0.0001622359,0.0001646222],"domain_scores_gemma":[0.9992058,0.0002110292,0.0001067261,0.0001139288,0.0002388568,0.0001236645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001214519,0.0003156904,0.005258667,0.00009383433,0.00005290587,1.565125e-7,0.01315711,3.744161e-7,0.0002106274,0.003517801,0.05222474,0.9250466],"study_design_scores_gemma":[0.001845374,0.0008601886,0.6756623,0.000640475,0.000217389,0.00002447611,0.1259514,0.0008137102,0.007881088,0.01240668,0.1730549,0.0006420481],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9573216,0.00004863978,0.03315718,0.0048781,0.003179896,0.001223512,0.000003822204,0.0000359423,0.0001512507],"genre_scores_gemma":[0.9749019,0.0002405993,0.01565793,0.002104368,0.001051997,0.0005021376,0.0004787504,0.00002195996,0.005040422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9244046,"threshold_uncertainty_score":0.3624883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1915809363432423,"score_gpt":0.5105255375218872,"score_spread":0.3189446011786449,"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."}}