{"id":"W4412964784","doi":"10.1007/978-3-031-93688-3_14","title":"A Transfer Learning Approach for Emotion Recognition Integrated with Cognitive Evaluation in Virtual Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Transfer of learning; Computer science; Cognition; Artificial intelligence; Human–computer interaction; Cognitive science; Information retrieval; Psychology; Neuroscience","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":[0.002249472,0.0002263572,0.0002583072,0.001714961,0.0003930859,0.00017385,0.0003482324,0.0002410775,0.0000676406],"category_scores_gemma":[0.000150016,0.0002242502,0.0000460994,0.0005534254,0.000458137,0.002294436,0.0001094487,0.0008649423,0.00002386772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002102977,"about_ca_system_score_gemma":0.0002876354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000227993,"about_ca_topic_score_gemma":0.00002387145,"domain_scores_codex":[0.9982557,0.0002150513,0.0006444731,0.0003388972,0.0003311004,0.0002147405],"domain_scores_gemma":[0.9979654,0.0003431435,0.0002114469,0.0003222141,0.001113793,0.00004398823],"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":[0.0001054368,0.00006590928,0.00004741769,0.00004366026,0.00001921899,1.0892e-7,0.006109809,0.002202459,0.000002828465,0.02580744,0.00002669651,0.965569],"study_design_scores_gemma":[0.005780381,0.0008785676,0.001931542,0.002166252,0.000134271,0.0000321845,0.005522097,0.9596664,0.00001993866,0.001838617,0.02129291,0.0007367837],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003232384,0.0001543534,0.6231042,0.0001303057,0.0001982442,0.001950829,0.00003924848,0.00008303387,0.3711075],"genre_scores_gemma":[0.9661435,0.0009908567,0.01569964,0.0006525864,0.00004921767,0.000939336,0.008263522,0.00003093157,0.007230346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9648322,"threshold_uncertainty_score":0.9144658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0897589473525127,"score_gpt":0.3457357169094659,"score_spread":0.2559767695569531,"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."}}