{"id":"W2779957450","doi":"","title":"Identifying correlation between facial expression and heart rate and skin conductance with iMotions biometric platform","year":2017,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Sadness; Skin conductance; Facial expression; Anger; Disgust; Heart rate variability; Biometrics; Stimulus (psychology); Heart rate; Psychology; Psychophysiology; Contempt; Audiology; Cognitive psychology; Communication; Artificial intelligence; Computer science; Neuroscience; Social psychology; Medicine; Internal medicine","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":[0.0002794818,0.0003610116,0.000341408,0.0006074871,0.00008249866,0.0002540181,0.0001733778,0.0003792651,0.002032],"category_scores_gemma":[0.0010561,0.0001195489,0.000208106,0.0003783682,0.0001161147,0.0002580049,0.0002853642,0.0002237481,0.0006457271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008838202,"about_ca_system_score_gemma":0.00006705093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003221913,"about_ca_topic_score_gemma":0.0005428334,"domain_scores_codex":[0.9996462,0.00008029424,0.00002097759,0.0001038659,0.0001144322,0.00003429601],"domain_scores_gemma":[0.9996917,0.00008463366,0.00008197079,0.00003516715,0.00008138332,0.00002514762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001667013,0.0002898752,0.2101688,0.0005811967,0.0002057579,0.0006390067,0.0006892863,0.001714985,0.5275528,0.0004542325,0.00290902,0.253128],"study_design_scores_gemma":[0.00003844105,0.0008604173,0.8909882,0.00005535109,0.0001599079,0.002820261,0.0003943061,0.02482235,0.07668257,0.0003677631,0.002748243,0.00006216612],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9570254,0.0003357958,0.03797143,0.0000918399,0.00006669946,0.0001180379,0.001164207,0.0004211072,0.002805542],"genre_scores_gemma":[0.9816171,0.0002119708,0.01598597,0.00004987627,0.00004108971,0.0001211607,0.0005479042,0.00003153689,0.001393321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002032,"threshold_uncertainty_score":0.006797731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1035749526435175,"score_gpt":0.3620560583710472,"score_spread":0.2584811057275297,"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."}}