{"id":"W4404031975","doi":"10.1109/icccnt61001.2024.10725638","title":"Multimodal Emotion Recognition Using Computer Vision: A Comprehensive Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Emotion recognition; Artificial intelligence; Computer vision; Human–computer interaction; Speech recognition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007731849,0.0001571027,0.0001560935,0.0001695974,0.00004711919,0.0001248222,0.00005337886,0.0000996977,0.00006988192],"category_scores_gemma":[0.000001381281,0.0001464269,0.00007706757,0.0002420368,0.00001777851,0.0002342231,0.00002074997,0.0001564239,0.0003811947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169708,"about_ca_system_score_gemma":0.00001062745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003539706,"about_ca_topic_score_gemma":0.000001621725,"domain_scores_codex":[0.9991841,0.00003892377,0.0002095906,0.0002221614,0.0001513383,0.0001938423],"domain_scores_gemma":[0.9997061,0.0000423803,0.000009918148,0.0001354394,0.0000515436,0.00005460768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002347562,0.0001141931,0.00007500871,0.002790881,0.0003444048,0.0001231494,0.001890923,0.6318893,0.04226884,0.0003133131,0.01756436,0.3026021],"study_design_scores_gemma":[0.0001690922,0.0000296019,0.0001695887,0.0001505712,0.00001084999,0.00006986819,0.00009156544,0.9961281,0.0006566981,0.00002605568,0.00230508,0.0001928672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.32789,0.0002786012,0.66379,0.00001260459,0.002230277,0.0002641506,0.00001032828,0.001237481,0.004286512],"genre_scores_gemma":[0.9427431,0.000005030368,0.05633568,0.00002686543,0.0007142971,0.000008707522,0.00007548211,0.00005028425,0.00004052951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6148531,"threshold_uncertainty_score":0.5971115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02837219221057608,"score_gpt":0.2453677409923563,"score_spread":0.2169955487817802,"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."}}