{"id":"W2061434485","doi":"10.1007/978-3-642-31454-4_28","title":"Automating the Modeling of Learners’ Erroneous Behaviors in Model-Tracing Tutors","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Tracing; Human–computer interaction; Artificial intelligence; Programming language; Software 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002617724,0.001189727,0.00112043,0.0007905738,0.0005504783,0.002053051,0.002675009,0.001410143,0.002196047],"category_scores_gemma":[0.02315077,0.0006754842,0.0006634156,0.0004078199,0.0006572655,0.002276452,0.002535086,0.001814264,0.0007302347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001374945,"about_ca_system_score_gemma":0.002251932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008316668,"about_ca_topic_score_gemma":0.007015053,"domain_scores_codex":[0.9979452,0.0007891019,0.000147476,0.0004827568,0.0004981069,0.0001372967],"domain_scores_gemma":[0.9875758,0.006952691,0.001144603,0.002061118,0.00191675,0.0003491696],"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":[0.001200508,0.0004711628,0.03105871,0.00029949,0.0001611967,0.0004633574,0.002469643,0.6680443,0.02183372,0.007642827,0.002280379,0.2640748],"study_design_scores_gemma":[0.000009395809,0.00003952469,0.0004024694,0.000008996138,0.00001654247,0.0000348709,0.00003960872,0.9909055,0.006383547,0.001793853,0.0003564952,0.000009043716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1739029,0.0001117616,0.813947,0.0001885731,0.00004782766,0.0001577323,0.0001514722,0.01016479,0.001327917],"genre_scores_gemma":[0.8639228,0.00005642971,0.1338614,0.00004463953,0.000009506734,0.00008034771,0.0001789523,0.0004401662,0.00140571],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008316668,"threshold_uncertainty_score":0.01653653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03079213957600865,"score_gpt":0.2591446919094001,"score_spread":0.2283525523333914,"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."}}