{"id":"W2624398640","doi":"","title":"Exploring Eye Tracking to Increase Bandwidth in User Modeling","year":2005,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Eye tracking; User modeling; Bandwidth (computing); User interface; User interface design; Cognition; User experience design; Artificial intelligence; Telecommunications","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001974036,0.00009076481,0.000113078,0.0001387314,0.0001464092,0.0001884571,0.00008406152,0.00001342634,0.002066052],"category_scores_gemma":[0.00002368279,0.00008021493,0.00003475347,0.00003963849,0.00001410735,0.0007134241,0.00003909978,0.00008811928,0.0002148707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005059217,"about_ca_system_score_gemma":0.00001344739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003205508,"about_ca_topic_score_gemma":0.08028541,"domain_scores_codex":[0.9992998,0.00002169451,0.0001973817,0.0001574609,0.0001139865,0.000209671],"domain_scores_gemma":[0.9997365,0.0000147898,0.00001418243,0.0001014938,0.00005404934,0.00007902078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001267409,0.0007229227,0.0200751,0.00006660594,0.00006984024,0.00004577144,0.1769902,0.07238717,0.002295513,0.656234,0.003782392,0.06720374],"study_design_scores_gemma":[0.00156435,0.0001334166,0.006570027,0.0002230978,0.00002740044,0.000001146928,0.01451759,0.1609633,0.002676892,0.002556036,0.8095824,0.001184398],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9392765,0.00001407508,0.0001378929,0.000618701,0.0001221542,0.00009484989,0.000001911346,0.00004321795,0.05969067],"genre_scores_gemma":[0.9919066,0.00001426776,0.0001530559,0.0005386361,0.0004877772,0.00002506165,0.000001402874,0.00001276632,0.006860392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8058,"threshold_uncertainty_score":0.9988462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1715340051628593,"score_gpt":0.2879757338273465,"score_spread":0.1164417286644872,"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."}}