{"id":"W1570452348","doi":"10.4101/jvwr.v2i2.707","title":"Development of Virtual Patient Simulations for Medical Education","year":2009,"lang":"en","type":"article","venue":"Journal of Virtual Worlds Research","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"","keywords":"Virtual patient; Perspective (graphical); Instructional simulation; Medical diagnosis; Conversation; Metaverse; Fidelity; Virtual reality; Computer science; Virtual world; Virtual machine; Principal (computer security); Human–computer interaction; Medical education; Multimedia; Psychology; Medicine; 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":[0.002437777,0.0001060575,0.0002434115,0.0006815431,0.000263264,0.0001080946,0.001040157,0.00009183858,0.00004490337],"category_scores_gemma":[0.001960725,0.00008727985,0.0001022557,0.001073929,0.00008671229,0.0004958601,0.0001375495,0.0004000135,0.00001039238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002047196,"about_ca_system_score_gemma":0.004235868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003757072,"about_ca_topic_score_gemma":0.0000178634,"domain_scores_codex":[0.9964493,0.0001558993,0.0009556655,0.0001874253,0.001907983,0.0003437564],"domain_scores_gemma":[0.9966008,0.0005982002,0.0003256015,0.0003559028,0.001682088,0.0004373925],"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":[0.00006048588,0.0009903227,0.00001403959,0.000006187523,0.00002211308,0.000001231003,0.002101607,0.0003571746,0.003286423,0.1049939,0.006440663,0.8817258],"study_design_scores_gemma":[0.005337597,0.02095392,0.02040215,0.001502921,0.00004482355,0.0002043305,0.004800254,0.1208148,0.06400266,0.0659118,0.6948487,0.001176033],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3815206,0.0001916796,0.6048371,0.0109087,0.0003419337,0.0005736744,0.000007165761,0.0000191749,0.001599942],"genre_scores_gemma":[0.9574941,0.00002435286,0.04176753,0.0002912768,0.0001490009,0.000009478638,0.000004361608,0.000006395116,0.0002535274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8805498,"threshold_uncertainty_score":0.7514248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06902581549803818,"score_gpt":0.4314993517541319,"score_spread":0.3624735362560937,"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."}}