{"id":"W4390971319","doi":"10.1109/bibm58861.2023.10385256","title":"Pain Management and Conditioning through Virtual Reality and Affective Computing","year":2023,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Virtual reality; Computer science; Conditioning; Human–computer interaction; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004293316,0.0002575679,0.000226321,0.0001960776,0.0001451854,0.0007794581,0.0002761571,0.00026172,0.002298218],"category_scores_gemma":[0.001447642,0.0001029031,0.0003000651,0.0001429508,0.0003623235,0.0003457013,0.000568728,0.000347076,0.0002128963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205809,"about_ca_system_score_gemma":0.0001430884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002933922,"about_ca_topic_score_gemma":0.0003937801,"domain_scores_codex":[0.9994509,0.0002788918,0.00001909017,0.00005453637,0.0001376359,0.0000590234],"domain_scores_gemma":[0.999639,0.000245899,0.00004434745,0.00002644622,0.00002122087,0.00002309562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0023431,0.002372709,0.007267667,0.00142214,0.0003264266,0.0002103378,0.001908883,0.01183221,0.2223316,0.00719583,0.002100117,0.740689],"study_design_scores_gemma":[0.002499763,0.04282541,0.4142989,0.001810257,0.002670405,0.006584416,0.007242257,0.198837,0.1796249,0.04484811,0.09805145,0.000707138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8538622,0.008544258,0.1068497,0.001092888,0.0002736695,0.0003045867,0.00009723051,0.0002416118,0.02873382],"genre_scores_gemma":[0.977441,0.00170711,0.01860287,0.0003283724,0.00008694301,0.0001298743,0.000030231,0.00001334821,0.001660321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002298218,"threshold_uncertainty_score":0.007688284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04568400982105314,"score_gpt":0.3461234661862813,"score_spread":0.3004394563652281,"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."}}