{"id":"W2033764444","doi":"10.1145/381234.381246","title":"Designing intelligent tutoring systems","year":2001,"lang":"en","type":"article","venue":"ACM SIGCUE Outlook","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; TUTOR; Architecture; Human–computer interaction; Intelligent decision support system; Intelligent tutoring system; Interface (matter); Curriculum; Multimedia; Software engineering; Artificial intelligence","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00076969,0.0002648983,0.0002973259,0.0001812395,0.0002995989,0.0005160295,0.001711571,0.0001007535,0.00002352238],"category_scores_gemma":[0.0003272153,0.0002478725,0.0001199388,0.0003824712,0.00002492302,0.0005879804,0.0005235776,0.0003067072,0.0008106268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001759489,"about_ca_system_score_gemma":0.0000646977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002310997,"about_ca_topic_score_gemma":0.00000237688,"domain_scores_codex":[0.9977398,0.000155964,0.0004466277,0.0005815058,0.000454664,0.000621456],"domain_scores_gemma":[0.9980297,0.0002894891,0.0001812517,0.001176516,0.0001516286,0.0001713855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002580759,0.000178052,0.03981197,0.0001629443,0.0002411632,0.0009972572,0.00958863,0.02853657,0.02896759,0.8136299,0.002688499,0.07517166],"study_design_scores_gemma":[0.0003148855,0.00020999,0.0008972831,0.0005629734,0.00001859104,0.0003429276,0.001012505,0.01725538,0.01535654,0.0009247918,0.9621714,0.000932709],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01215301,0.001128716,0.9736811,0.0002155485,0.002955867,0.0002832895,3.696595e-7,0.0005585889,0.009023504],"genre_scores_gemma":[0.9249165,0.00007570893,0.02040644,0.000139459,0.000961883,0.0000541256,0.000001586301,0.00004241741,0.05340187],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9594829,"threshold_uncertainty_score":0.9999974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04199488165992046,"score_gpt":0.2634949553067589,"score_spread":0.2215000736468384,"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."}}