{"id":"W4387951256","doi":"10.1109/ccece58730.2023.10288951","title":"Lightweight Model for Emotion Detection from Facial Expression in Online Learning","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":"Athabasca University","funders":"","keywords":"Computer science; Facial expression; Deep learning; Architecture; Inference; Artificial intelligence; Process (computing); Face (sociological concept); Online learning; Enhanced Data Rates for GSM Evolution; Learning environment; Expression (computer science); State (computer science); Machine learning; Emotion recognition; Emotion detection; Affective computing; Multimedia; Mathematics education; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001321274,0.00008330931,0.00009755827,0.0002176871,0.00008200288,0.00001172599,0.00004128078,0.0001659195,0.000505959],"category_scores_gemma":[0.0000429646,0.00007700944,0.00005548753,0.0001827046,0.000008073559,0.00008905757,0.00001610247,0.00014932,0.0003750702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002650506,"about_ca_system_score_gemma":0.000005781385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006094644,"about_ca_topic_score_gemma":0.0003959755,"domain_scores_codex":[0.999231,0.00007036109,0.0001918766,0.0002533024,0.0000792241,0.0001742049],"domain_scores_gemma":[0.9997374,0.00006071398,0.00005102696,0.00008027184,0.00003423783,0.00003628013],"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":[0.0005452061,0.0006130766,0.002458899,0.00002546307,0.00003264208,0.000006912983,0.008622597,0.009280042,0.2737203,0.0003400259,0.005212823,0.699142],"study_design_scores_gemma":[0.003167354,0.0001843306,0.03967401,0.00006354579,0.00001647668,0.000001557708,0.002950863,0.9202723,0.02329339,0.006236814,0.003862498,0.0002768444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8095061,0.000007363084,0.1863724,0.0001615611,0.0009125485,0.0002291454,0.0000267595,0.0003003622,0.002483785],"genre_scores_gemma":[0.9801583,0.00001416251,0.001089057,0.00007551942,0.000236327,0.00006178681,0.0006237722,0.00001867471,0.01772236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9109923,"threshold_uncertainty_score":0.5539896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06111772261021102,"score_gpt":0.3373193236906229,"score_spread":0.2762016010804119,"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."}}