{"id":"W1518092398","doi":"10.1007/978-3-642-13437-1_46","title":"Using Emotional Coping Strategies in Intelligent Tutoring Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Emotional Intelligence and Performance","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Coping (psychology); Computer science; Anxiety; Intelligent tutoring system; Cognitive psychology; Human–computer interaction; Artificial intelligence; Psychology; Clinical 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007277596,0.0003572424,0.0003767151,0.0007718351,0.0001609212,0.0002712663,0.0008106147,0.0004511784,0.0003166732],"category_scores_gemma":[0.0000224878,0.0003449731,0.0000766496,0.0003048489,0.0005547706,0.0003394359,0.0001942917,0.001353796,0.0001275789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002970191,"about_ca_system_score_gemma":0.0004216778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003085372,"about_ca_topic_score_gemma":0.0002578967,"domain_scores_codex":[0.9974858,0.00002894872,0.0005799311,0.0008284244,0.0005473107,0.0005296442],"domain_scores_gemma":[0.998778,0.0002784661,0.0002095977,0.0004892452,0.0001625154,0.00008221602],"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":[0.00002656697,0.00007713708,0.002355448,0.0001949788,0.00003116343,0.0001969067,0.005044197,0.7019893,0.0009341739,0.2037417,0.000008077013,0.08540041],"study_design_scores_gemma":[0.0006529319,0.0004981903,0.005006695,0.009134028,0.0000355882,0.00120003,0.00004885701,0.6974894,0.003370206,0.267492,0.01162017,0.003451933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007784276,0.000946128,0.9706453,0.0000728395,0.009042106,0.0003069101,0.00000661407,0.00004257708,0.01115321],"genre_scores_gemma":[0.9629395,0.00008942243,0.03269086,0.0004041152,0.002697928,0.00001397376,0.00001537005,0.00005916908,0.001089689],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9551552,"threshold_uncertainty_score":0.9999002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09127022621146984,"score_gpt":0.3584669991288086,"score_spread":0.2671967729173388,"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."}}