{"id":"W2125190707","doi":"10.1109/icalt.2007.264","title":"Towards Advanced Learner Modeling: Discussions on Quasi Real-time Adaptation with Physiological Data","year":2007,"lang":"en","type":"article","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Adaptation (eye); Computer science; Relevance (law); Human–computer interaction; Data modeling; Artificial intelligence; Data science; Multimedia; Psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005657706,0.0001580466,0.0001684768,0.00006756627,0.0001880919,0.00008183663,0.0007997926,0.00005728266,0.00002563072],"category_scores_gemma":[0.0000592257,0.00008705479,0.00003254732,0.0002106436,0.00002072278,0.000508231,0.0002567597,0.0001932491,0.000158847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004114936,"about_ca_system_score_gemma":0.00004310948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001449255,"about_ca_topic_score_gemma":0.00001448587,"domain_scores_codex":[0.9984285,0.00006776263,0.0002285395,0.000589731,0.0003618347,0.0003236833],"domain_scores_gemma":[0.9988465,0.00006882662,0.00007825685,0.0008180377,0.00008806519,0.0001002537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001432755,0.0002823394,0.00003060117,0.00001192086,0.00003162025,0.00004042106,0.001380912,0.2908301,0.008594508,0.5563969,0.0003746326,0.1418827],"study_design_scores_gemma":[0.0001827004,0.0006248349,0.0003403677,0.00007596901,0.000004107388,0.000004906699,0.0004869629,0.9935548,0.00032528,0.0003117672,0.003856344,0.0002319078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02280734,0.000008226041,0.9639063,0.0003590789,0.000124436,0.0001357988,0.00000127495,0.0002843894,0.01237312],"genre_scores_gemma":[0.9018999,0.00000797041,0.08767907,0.00009838349,0.0001238226,0.000003855587,0.00001985258,0.0000118611,0.0101553],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8790925,"threshold_uncertainty_score":0.3549991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0926943128581264,"score_gpt":0.3122900178686184,"score_spread":0.219595705010492,"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."}}