{"id":"W3203891641","doi":"10.2196/32721","title":"Virtual Reality in Health Care: Bibliometric Analysis","year":2021,"lang":"en","type":"article","venue":"JMIR Serious Games","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"The Internet; Health care; Medical education; Public relations; Psychology; Political science; Medicine; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.0003997959,0.0001344711,0.0003505488,0.01720912,0.00009814298,0.000282092,0.0005544354,0.00006726233,0.00002330116],"category_scores_gemma":[0.000113897,0.000133596,0.0001334274,0.1999624,0.00003192812,0.0003498138,0.0002473659,0.0001491038,0.00003461628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002045248,"about_ca_system_score_gemma":0.0004466067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001153018,"about_ca_topic_score_gemma":0.00161077,"domain_scores_codex":[0.998121,0.000183979,0.0004087994,0.000515863,0.0003694253,0.0004009823],"domain_scores_gemma":[0.9983596,0.00009285994,0.0001349917,0.001040688,0.0001479977,0.0002239171],"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":[0.000005564642,0.0002737535,0.004391067,0.0000431374,0.0001011598,0.00003046668,0.003429202,0.001036822,0.0001538561,0.02288178,0.003755168,0.963898],"study_design_scores_gemma":[0.0004020096,0.0001980301,0.9141215,0.00001732193,0.00001568433,0.00001330989,0.0005651318,0.006647089,0.0004843673,0.0006257985,0.07662349,0.0002862894],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6873318,0.005078935,0.2810203,0.01975564,0.0002795986,0.0007343678,0.00006941456,0.0004423831,0.005287582],"genre_scores_gemma":[0.9956751,0.0004312768,0.002469245,0.001044261,0.00002932921,0.00005607043,0.00003597022,0.000006865563,0.0002518538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9636117,"threshold_uncertainty_score":0.99393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02382220927478649,"score_gpt":0.3358496085904542,"score_spread":0.3120273993156677,"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."}}