{"id":"W2085556084","doi":"10.1145/1056808.1056950","title":"eyeView","year":2005,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Videoconferencing; Focus (optics); Multimedia; Real estate; Human–computer interaction; Space (punctuation)","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":[0.0009413173,0.0008556177,0.0005676159,0.0009790713,0.0004616118,0.001953287,0.002389929,0.001360286,0.06588437],"category_scores_gemma":[0.002904884,0.0006467726,0.0006842652,0.0004170028,0.0003888006,0.002222406,0.002178491,0.001100908,0.01940356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000474981,"about_ca_system_score_gemma":0.000694843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001670589,"about_ca_topic_score_gemma":0.002692634,"domain_scores_codex":[0.9992785,0.0001045128,0.00004164055,0.000208977,0.0002821758,0.00008420025],"domain_scores_gemma":[0.998646,0.0003758301,0.00007041854,0.0002859696,0.0004536118,0.0001681488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001600615,0.0002484527,0.004641764,0.0009962037,0.0001604459,0.001103348,0.001024103,0.002907829,0.1267275,0.03220284,0.1450262,0.6833606],"study_design_scores_gemma":[0.0001961391,0.0004939932,0.003250067,0.0001974365,0.000148659,0.003536444,0.0002224747,0.02501731,0.07909305,0.006335788,0.881283,0.0002255837],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01693105,0.002815718,0.8513103,0.001091172,0.0008696117,0.0008036199,0.002537647,0.04026842,0.08337248],"genre_scores_gemma":[0.1637395,0.00318548,0.5920533,0.002824343,0.0003788125,0.001486694,0.006023582,0.01022117,0.2200872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06588437,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246714569755896,"score_gpt":0.2479995717306686,"score_spread":0.2355324260331096,"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."}}