{"id":"W4399209596","doi":"10.1007/978-3-031-63028-6_26","title":"Generating Learning Sequences Using Contextual Bandit Algorithms","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Computer science; Artificial intelligence; Algorithm; Machine learning","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":[0.001601653,0.001080582,0.001448442,0.001417091,0.001017865,0.001306508,0.002049808,0.001946066,0.008229604],"category_scores_gemma":[0.008746042,0.000992773,0.0009229041,0.001447775,0.0009938722,0.002300539,0.002402469,0.001893501,0.002140687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060941,"about_ca_system_score_gemma":0.001539609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006397271,"about_ca_topic_score_gemma":0.008457043,"domain_scores_codex":[0.9989644,0.0003280748,0.00007264777,0.0003259181,0.0001912923,0.0001176379],"domain_scores_gemma":[0.9940737,0.004261222,0.0002131914,0.0005444817,0.000731921,0.0001756152],"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":[0.0007246111,0.000322799,0.001656977,0.0002172598,0.00007556895,0.0001468739,0.0002659799,0.4644687,0.004434736,0.02531827,0.003645619,0.4987226],"study_design_scores_gemma":[0.00001874992,0.00003701935,0.00005885389,0.00001222555,0.000009492298,0.00001471438,0.00001210996,0.9915986,0.001259701,0.006597956,0.0003761195,0.000004487865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02569266,0.0001790448,0.969151,0.0001035879,0.0000436803,0.0001323212,0.0001060061,0.002346808,0.002244801],"genre_scores_gemma":[0.40326,0.0002035405,0.589743,0.0001423905,0.00006930933,0.0005919367,0.0008814004,0.000489215,0.004619292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008229604,"threshold_uncertainty_score":0.02753079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03510358810304304,"score_gpt":0.2734337686053945,"score_spread":0.2383301805023514,"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."}}