{"id":"W2400082606","doi":"","title":"User Task Adaptation in Multimedia Presentations.","year":2013,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of British Columbia","funders":"","keywords":"Computer science; Presentation (obstetrics); Graphics; Multimedia; Adaptation (eye); Visualization; Reading (process); Scrolling; Set (abstract data type); Artificial intelligence; Linguistics; Computer graphics (images)","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":[0.0002092864,0.0002141934,0.0001599203,0.0004511055,0.0001337488,0.0006283172,0.0004690698,0.00009949595,0.0003695241],"category_scores_gemma":[0.0001498616,0.000220002,0.00004210608,0.0003744679,0.00003732288,0.002202632,0.00006970485,0.0001305773,0.0001176615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006319812,"about_ca_system_score_gemma":0.0001496168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009626818,"about_ca_topic_score_gemma":0.0004795665,"domain_scores_codex":[0.9980473,0.0001090972,0.0004929311,0.0005229885,0.0006144274,0.0002132681],"domain_scores_gemma":[0.9984933,0.00007179978,0.0001791041,0.0002339338,0.000902474,0.0001194574],"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":[0.00002327894,0.0002365044,0.005102418,0.00002707442,0.0000479928,0.000003290542,0.01656378,0.1323128,0.0002754121,0.8293861,0.001935299,0.01408614],"study_design_scores_gemma":[0.0006835471,0.00003520584,0.002534676,0.00005477695,0.000006532519,0.000002904657,0.001705469,0.9866408,0.00001786913,0.006858133,0.001219173,0.0002409375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0118227,0.00003749264,0.9833367,0.001931242,0.0003344596,0.0003361793,0.00002101989,0.0001045221,0.002075695],"genre_scores_gemma":[0.9767387,0.0003745376,0.01933842,0.0009768504,0.00009301798,0.00009015997,0.0006167292,0.00001870142,0.001752923],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.964916,"threshold_uncertainty_score":0.8971419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09195351315500712,"score_gpt":0.3219189628515722,"score_spread":0.2299654496965651,"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."}}