{"id":"W3047490124","doi":"10.18280/ria.340304","title":"Performance Evaluation of Machine Learning for Recognizing Human Facial Emotions","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Facial expression; Human–computer interaction; Artificial intelligence; Machine learning; Psychology; Cognitive psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005820145,0.00172062,0.001475831,0.002704571,0.0006644888,0.001307752,0.001182223,0.0014249,0.001567225],"category_scores_gemma":[0.00949662,0.0002064719,0.0008277451,0.001534138,0.0004040092,0.001466835,0.0008699578,0.0007393542,0.001260046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358265,"about_ca_system_score_gemma":0.0007448341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007467044,"about_ca_topic_score_gemma":0.004316933,"domain_scores_codex":[0.9943299,0.001343103,0.0006532915,0.001050912,0.002060335,0.0005624922],"domain_scores_gemma":[0.9948237,0.002551283,0.000300509,0.0004239357,0.001685657,0.0002149651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004519845,0.001102927,0.04017102,0.001063787,0.0008826149,0.0002583075,0.0001576725,0.1063539,0.01440088,0.001021085,0.02588133,0.8041867],"study_design_scores_gemma":[0.0001041156,0.001596202,0.02988287,0.00007534806,0.0002019981,0.0002985208,0.0002310218,0.9401593,0.02188248,0.0007791388,0.004725039,0.00006397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8790411,0.02073494,0.07191409,0.001197541,0.001913015,0.0003710442,0.0037606,0.006483264,0.01458429],"genre_scores_gemma":[0.9573606,0.00155354,0.02811234,0.0001710538,0.0001902441,0.0001442863,0.008397287,0.0001365337,0.003934069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007467044,"threshold_uncertainty_score":0.0307802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1412725530523142,"score_gpt":0.3237512251745021,"score_spread":0.1824786721221879,"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."}}