{"id":"W2317376037","doi":"10.14288/1.0166864","title":"Eye-tracking as a source of information for automatically predicting user learning with MetaTutor, an intelligent tutoring system to support self-regulated learning","year":2014,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Tracking (education); Eye tracking; Intelligent tutoring system; Human–computer interaction; Artificial intelligence; Multimedia; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001317248,0.0001065533,0.0004533174,0.0001707114,0.0005369457,0.0004407271,0.0006533586,0.0001160584,0.000005421833],"category_scores_gemma":[0.0002206409,0.0002566109,0.0001267908,0.0004553214,0.00004782703,0.00176619,0.000219062,0.0002785494,0.00001591793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001703648,"about_ca_system_score_gemma":0.0001245659,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01280474,"about_ca_topic_score_gemma":0.001682494,"domain_scores_codex":[0.9979835,0.0002172793,0.0004212172,0.0004250994,0.0005339202,0.0004190051],"domain_scores_gemma":[0.9979612,0.0001617206,0.0005776369,0.0003138713,0.0007802243,0.0002053648],"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":[0.00005872366,0.0001482288,0.06431758,0.001758528,0.0003610871,0.00003681098,0.03030969,0.1563226,0.001236173,0.002517599,0.00002865617,0.7429043],"study_design_scores_gemma":[0.001172074,0.002833546,0.4274896,0.002578504,0.0001354112,0.000169264,0.01664973,0.5337175,0.0001335427,0.0000198636,0.01441733,0.0006836131],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.52578,0.000003627469,0.4732311,0.000007418575,0.00009533622,0.0002845428,0.000001075188,0.0003479079,0.0002490637],"genre_scores_gemma":[0.9682418,0.000001059568,0.0305872,0.00001004782,0.00004671443,0.000003079243,0.000009649974,0.00002211773,0.001078331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7422207,"threshold_uncertainty_score":0.9999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006591483274655736,"score_gpt":0.1943418476888416,"score_spread":0.1877503644141858,"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."}}