{"id":"W2408389737","doi":"","title":"When to Adapt: Detecting User's Confusion During Visualization Processing.","year":2013,"lang":"en","type":"article","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of British Columbia","funders":"","keywords":"Confusion; Computer science; Visualization; Human–computer interaction; Data visualization; Artificial intelligence; Psychology","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":[0.002239393,0.0007834694,0.0005458483,0.001356256,0.0004035654,0.001273749,0.0006551804,0.001056533,0.001565444],"category_scores_gemma":[0.03399672,0.0002698551,0.0002293829,0.0005488919,0.0002824695,0.001444303,0.0009568558,0.0008725849,0.000991063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002940317,"about_ca_system_score_gemma":0.000318019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001084429,"about_ca_topic_score_gemma":0.00228938,"domain_scores_codex":[0.9983351,0.0007283125,0.0001398776,0.0003019731,0.0003873956,0.0001074574],"domain_scores_gemma":[0.9801587,0.01321779,0.002062695,0.001442684,0.002246602,0.0008716584],"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":[0.005296636,0.0009323634,0.2861851,0.001240793,0.0002961085,0.001161696,0.01122912,0.004670887,0.1714625,0.0007285635,0.01743696,0.4993594],"study_design_scores_gemma":[0.00011705,0.002435565,0.7234439,0.0003211091,0.0003056981,0.002253271,0.003787823,0.1532579,0.0948465,0.004723269,0.01410897,0.0003989188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9256162,0.0008882173,0.05996984,0.0005602895,0.0001492161,0.0005185931,0.00320838,0.006429791,0.002659447],"genre_scores_gemma":[0.9669562,0.0001677563,0.03057982,0.0001526172,0.00003749769,0.0001732003,0.001114057,0.0001584659,0.000660424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002239393,"threshold_uncertainty_score":0.01184314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01568163846183473,"score_gpt":0.2465419027506995,"score_spread":0.2308602642888648,"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."}}