{"id":"W4321020753","doi":"10.1109/fg57933.2023.10042502","title":"Pain Detection in Masked Faces during Procedural Sedation","year":2023,"lang":"en","type":"article","venue":"","topic":"Anesthesia and Sedative Agents","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Sedation; Artificial intelligence; Computer science; Medicine; Face (sociological concept); Receiver operating characteristic; Anesthesia; Machine learning","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":[0.000605301,0.0004889055,0.0003798787,0.0003232981,0.0001915547,0.0003910854,0.0002648212,0.0004766145,0.001499782],"category_scores_gemma":[0.004471843,0.0001201978,0.0003881864,0.0001488427,0.0002341162,0.0003287193,0.0004374103,0.0004606177,0.0003800463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000289392,"about_ca_system_score_gemma":0.0003164849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00213547,"about_ca_topic_score_gemma":0.004132007,"domain_scores_codex":[0.9993762,0.0001493161,0.00002856529,0.0001375304,0.0002241785,0.00008418287],"domain_scores_gemma":[0.9990047,0.0005527828,0.00015229,0.00007901886,0.0001750644,0.00003612059],"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":[0.006714564,0.0006084818,0.07070243,0.0009125695,0.0003925839,0.001407453,0.001010978,0.03369148,0.2983593,0.000950247,0.01441146,0.5708385],"study_design_scores_gemma":[0.0001297303,0.002337227,0.457367,0.0002598126,0.0003404434,0.005879318,0.000899753,0.3910164,0.1272529,0.003237587,0.01110186,0.0001780362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9602287,0.001005924,0.03156274,0.0003976497,0.0002581623,0.0001931204,0.001728506,0.0004790505,0.004146145],"genre_scores_gemma":[0.9793241,0.0004214509,0.01690335,0.0002608357,0.00008159663,0.0000717357,0.001444154,0.00003858894,0.001454258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00213547,"threshold_uncertainty_score":0.005017221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02127268147643905,"score_gpt":0.2727144293892972,"score_spread":0.2514417479128581,"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."}}