{"id":"W2171866551","doi":"10.1145/985921.986005","title":"Attentive display","year":2004,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Gaze; Visualization; Human–computer interaction; Point (geometry); Display device; Computer graphics (images); Point of interest; Computer vision; Artificial intelligence","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":[0.0002905858,0.0006994638,0.0002794384,0.0004214391,0.0003817196,0.00127848,0.001310409,0.000694896,0.02519647],"category_scores_gemma":[0.001977852,0.0002931902,0.0003535874,0.0002191562,0.0004181291,0.0013458,0.00169688,0.0006740771,0.00325257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002715466,"about_ca_system_score_gemma":0.0002123807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00109408,"about_ca_topic_score_gemma":0.0008374135,"domain_scores_codex":[0.9997038,0.00005512738,0.00001363121,0.0000751355,0.0001131989,0.00003912313],"domain_scores_gemma":[0.9991753,0.0003844617,0.00003915666,0.0001539348,0.0001750355,0.00007204739],"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":[0.001932138,0.0002992317,0.003219957,0.00131689,0.0001367243,0.002073512,0.003160945,0.003068745,0.3690239,0.02936061,0.04876286,0.5376445],"study_design_scores_gemma":[0.0004425669,0.002973249,0.02125007,0.0005242254,0.0005486348,0.006266102,0.001162114,0.04373606,0.2182283,0.0181468,0.6863639,0.0003580335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1691123,0.003756541,0.665643,0.001051124,0.001357587,0.000897128,0.0009750331,0.02068501,0.1365222],"genre_scores_gemma":[0.6559749,0.002067152,0.2468384,0.002233891,0.0005573223,0.0007459568,0.00115304,0.001329556,0.08909977],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02519647,"threshold_uncertainty_score":0.08429056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009593702746351442,"score_gpt":0.2301697970867651,"score_spread":0.2205760943404137,"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."}}