{"id":"W2399280070","doi":"","title":"Data mining techniques for design of ITS student models","year":2012,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Association rule learning; Cluster analysis; Machine learning; Task (project management); Intelligent tutoring system; Bayesian network; Data stream mining; Educational data mining; Data mining; Artificial intelligence; Data science; Engineering","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":[0.002352824,0.00018207,0.00034638,0.0002394528,0.0003160676,0.00003807784,0.002565979,0.000146977,0.00001833492],"category_scores_gemma":[0.00009527065,0.0002117347,0.0001150654,0.000287716,0.00005731681,0.003130527,0.001286884,0.0001927155,0.00001433766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008823293,"about_ca_system_score_gemma":0.00007404317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001651717,"about_ca_topic_score_gemma":0.000004332761,"domain_scores_codex":[0.9981735,0.0002141745,0.0002569591,0.0004395608,0.0004745859,0.0004411832],"domain_scores_gemma":[0.9979734,0.0002548229,0.0003815878,0.000953556,0.0002921705,0.0001444206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009549267,0.002445058,0.1675721,0.001796636,0.001662724,0.0000613376,0.09215521,0.01029831,0.2068389,0.4499585,0.003661747,0.06259453],"study_design_scores_gemma":[0.008579755,0.004388337,0.1554993,0.00545648,0.001068949,0.0001878671,0.03075633,0.2348498,0.3180022,0.004487792,0.2300853,0.006637944],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1434821,0.0004937677,0.8543907,0.0001000456,0.00024633,0.0005215161,0.00004516783,0.0001116831,0.0006086807],"genre_scores_gemma":[0.7973822,0.00002279962,0.1997876,0.00001986403,0.00008528538,0.00000114393,0.00001129348,0.00001578841,0.002674063],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6546032,"threshold_uncertainty_score":0.8634289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1584383268757932,"score_gpt":0.3022004124594734,"score_spread":0.1437620855836802,"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."}}