{"id":"W2246410247","doi":"","title":"Inducing optimal emotional state for learning in Intelligent Tutoring Systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Intelligent tutoring system; Artificial intelligence; Classifier (UML); Cognition; State (computer science); Emotional behavior; Naive Bayes classifier; Personality; Machine learning; Psychology; Support vector machine; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097154,0.000352184,0.0004131357,0.0002251665,0.0002631537,0.0007450106,0.0004303946,0.0005840192,0.001838993],"category_scores_gemma":[0.006316818,0.0002597688,0.0002283059,0.0001250419,0.0005306519,0.0008986138,0.001262757,0.0008272396,0.0003021945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005386147,"about_ca_system_score_gemma":0.0003304884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004150308,"about_ca_topic_score_gemma":0.0008880736,"domain_scores_codex":[0.9995081,0.0002289581,0.0000230091,0.0001157102,0.00004931463,0.00007487111],"domain_scores_gemma":[0.9986254,0.0008997339,0.0001241943,0.0001148814,0.0001616128,0.00007414078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001919829,0.001027215,0.01081548,0.0002305882,0.0001036775,0.0001332509,0.0008935979,0.4103751,0.0772097,0.02276358,0.003723816,0.4708042],"study_design_scores_gemma":[0.00004508754,0.0001367646,0.001340275,0.00001044646,0.00001784011,0.00001439329,0.00009704549,0.973657,0.01239747,0.01187449,0.0003986949,0.00001047729],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4876283,0.0001726742,0.5069184,0.0004201756,0.00006249739,0.0001125398,0.0001030786,0.0006808985,0.003901528],"genre_scores_gemma":[0.97031,0.00003013699,0.02869238,0.00004871306,0.00001110252,0.00006099542,0.00008571663,0.00003567515,0.0007253468],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001838993,"threshold_uncertainty_score":0.006152034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05595247406593911,"score_gpt":0.2653891540998218,"score_spread":0.2094366800338827,"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."}}