{"id":"W4411409730","doi":"10.1109/icdcece65353.2025.11035431","title":"Multimodal Emotion Recognition using Multi-Strategy Opposite Learning with Lyrebird Optimization Algorithm","year":2025,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Emotion recognition; Optimization algorithm; Artificial intelligence; Speech recognition; Algorithm; Mathematical optimization; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008358003,0.0007445702,0.0008211976,0.0005477337,0.0003668696,0.0007811859,0.0007211108,0.0009023211,0.002181851],"category_scores_gemma":[0.00140155,0.0002633081,0.0008251776,0.000348735,0.0003730036,0.0005358676,0.0007923133,0.0007596876,0.0005184393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004265101,"about_ca_system_score_gemma":0.0006389012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003706235,"about_ca_topic_score_gemma":0.002767743,"domain_scores_codex":[0.9996179,0.0001100112,0.00003185654,0.00009942213,0.00008715462,0.00005371064],"domain_scores_gemma":[0.9997019,0.0001360213,0.00003308193,0.00001854672,0.00009318307,0.00001717065],"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":[0.0003412329,0.0002867389,0.003115929,0.0001375316,0.0001697788,0.0001415927,0.0001425273,0.4907186,0.0158829,0.005226708,0.003384933,0.4804515],"study_design_scores_gemma":[0.000006128871,0.00003389392,0.0001674353,0.000002716917,0.000005440422,0.00001132227,0.000007429767,0.9986436,0.0005688414,0.0003726181,0.0001765874,0.00000395334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0269463,0.000266545,0.9694558,0.0001656476,0.00003674707,0.00007317067,0.00002755254,0.0004619147,0.002566321],"genre_scores_gemma":[0.5732656,0.0002568912,0.4204126,0.0003597811,0.00004443807,0.0003810975,0.0002847832,0.0001012368,0.00489358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003706235,"threshold_uncertainty_score":0.007369339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05434739983268579,"score_gpt":0.3317963440410818,"score_spread":0.277448944208396,"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."}}