{"id":"W4310841718","doi":"10.3390/ecsa-9-13358","title":"Prediction of Emotional Measures via Electrodermal Activity (EDA) and Electrocardiogram (ECG)","year":2022,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa; Université du Québec en Outaouais","funders":"Canada Research Chairs","keywords":"Arousal; Valence (chemistry); Computer science; Affective computing; Emotional valence; Artificial intelligence; Emotion recognition; Pattern recognition (psychology); Speech recognition; Psychology; Cognition; Social psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004091864,0.0009989034,0.0004547783,0.000774383,0.0001038548,0.0005874845,0.0003287886,0.0005315309,0.001057222],"category_scores_gemma":[0.001659422,0.0001335501,0.0004535213,0.0005072518,0.0001123777,0.0004129028,0.0003080425,0.0006109526,0.0009756353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001274916,"about_ca_system_score_gemma":0.0001052865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001025834,"about_ca_topic_score_gemma":0.00163996,"domain_scores_codex":[0.9997357,0.00004970647,0.00001550479,0.000106632,0.00006058858,0.00003191743],"domain_scores_gemma":[0.9996219,0.0001227277,0.00006327948,0.00005091574,0.0001144507,0.00002680132],"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":[0.000845602,0.0005758624,0.06930406,0.0003007841,0.0003081117,0.0004094258,0.0001835576,0.06312835,0.1435796,0.0009913979,0.008636516,0.7117368],"study_design_scores_gemma":[0.00003348247,0.0004438574,0.1931472,0.00006222109,0.0001383887,0.0005595037,0.0001724093,0.7482891,0.05052367,0.002591386,0.003974258,0.00006451657],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4893089,0.001477636,0.4958413,0.0003782899,0.0002926299,0.0001430089,0.003589007,0.003773845,0.005195279],"genre_scores_gemma":[0.9113786,0.0006176397,0.08162803,0.00007621702,0.0001244621,0.00008631028,0.003235108,0.0001041671,0.002749483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001057222,"threshold_uncertainty_score":0.003536701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03170899537292664,"score_gpt":0.2683546106817604,"score_spread":0.2366456153088338,"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."}}