{"id":"W4406600009","doi":"10.58459/icce.2012.547","title":"Intelligent feedback polarity and timing selection in the Shufti Intelligent Tutoring System","year":2012,"lang":"en","type":"article","venue":"International Conference on Computers in Education","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Innovates","funders":"","keywords":"Polarity (international relations); Selection (genetic algorithm); Computer science; Intelligent tutoring system; Human–computer interaction; Multimedia; Artificial intelligence; Biology","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":[0.0008046377,0.0003977692,0.0005781166,0.0003945959,0.0003523603,0.0006416163,0.001188754,0.0006557373,0.002803611],"category_scores_gemma":[0.002735131,0.0002092896,0.0001837047,0.0002052647,0.0003396588,0.00061659,0.0005773429,0.0004969834,0.0007567461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000457392,"about_ca_system_score_gemma":0.0007033334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001933972,"about_ca_topic_score_gemma":0.00175638,"domain_scores_codex":[0.9995454,0.0001292966,0.00004088479,0.0001070916,0.0001124678,0.00006482274],"domain_scores_gemma":[0.9991411,0.000434892,0.00007858158,0.00005526322,0.0002166748,0.00007343956],"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":[0.001427127,0.0004712392,0.005509426,0.0002713909,0.00005667912,0.000463534,0.001097853,0.1190151,0.09107163,0.007047235,0.004514051,0.7690548],"study_design_scores_gemma":[0.0001779372,0.0006060578,0.002235188,0.0000276185,0.00008368326,0.0003843558,0.00007621896,0.943608,0.04209818,0.002704615,0.007936682,0.00006147966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1975931,0.0002820666,0.7841678,0.0002784093,0.00007592632,0.0003947171,0.0001083044,0.009764966,0.007334695],"genre_scores_gemma":[0.8203885,0.0001065894,0.1743386,0.0001030176,0.00003364293,0.000201534,0.0001095376,0.0001121643,0.004606416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002803611,"threshold_uncertainty_score":0.009379029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06307443679761048,"score_gpt":0.3178809975000718,"score_spread":0.2548065607024613,"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."}}