{"id":"W2300247546","doi":"","title":"An Adaptive Comprehension Assistant","year":2006,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Comprehension; Computer science; Artificial intelligence; Programming language","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":[0.0006501476,0.001270822,0.0006544504,0.0006525606,0.0004565517,0.001299507,0.001332597,0.001499698,0.0308147],"category_scores_gemma":[0.005067438,0.0003978856,0.0004310661,0.0003528003,0.0002652091,0.002875838,0.001413893,0.00105701,0.01085272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000199472,"about_ca_system_score_gemma":0.0004573024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002960483,"about_ca_topic_score_gemma":0.0003454295,"domain_scores_codex":[0.9993896,0.0001260649,0.00004725628,0.0002649888,0.0001417536,0.00003019312],"domain_scores_gemma":[0.9980583,0.001002764,0.0000870281,0.0002683585,0.0004620959,0.0001215232],"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":[0.0006888412,0.0005797732,0.001635528,0.0005154684,0.00006372222,0.001074364,0.001277893,0.001325034,0.1396826,0.00513663,0.02274795,0.825272],"study_design_scores_gemma":[0.0006210238,0.002159094,0.007539078,0.0001600929,0.0006213055,0.009014043,0.001271334,0.1937847,0.3533596,0.0145915,0.4166456,0.0002326721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05454812,0.000393702,0.8535582,0.0004948934,0.0004620253,0.0004832817,0.0006081004,0.06734185,0.0221098],"genre_scores_gemma":[0.3095455,0.0004911381,0.6045169,0.0009417768,0.0003378933,0.0006064292,0.00204243,0.00166603,0.07985185],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0308147,"threshold_uncertainty_score":0.1030855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03178084178120133,"score_gpt":0.261501101648632,"score_spread":0.2297202598674307,"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."}}