{"id":"W4253943720","doi":"10.1145/766084.766086","title":"AuraMirror","year":2003,"lang":"en","type":"article","venue":"CHI '03 extended abstracts on Human factors in computer systems - CHI '03","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Human–computer interaction; Process (computing); Painting; Visualization; Computer graphics (images); Multimedia; Artificial intelligence; Operating system; Visual arts; Art","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":[0.0006133518,0.001050161,0.000576584,0.0007518618,0.0006534019,0.002085632,0.002059108,0.001017976,0.05919057],"category_scores_gemma":[0.002263968,0.0004863177,0.0009710366,0.0004657063,0.0003856301,0.002605479,0.002865031,0.001246249,0.01805141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003978697,"about_ca_system_score_gemma":0.0006108391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003553733,"about_ca_topic_score_gemma":0.004066687,"domain_scores_codex":[0.9993809,0.00007317862,0.00003114998,0.0001490137,0.0002727553,0.00009300659],"domain_scores_gemma":[0.9991845,0.0001765207,0.00004743571,0.0002598555,0.0001738668,0.0001577052],"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":[0.002172487,0.0002730836,0.003419225,0.0009677786,0.0001350873,0.0006417036,0.001053141,0.002497353,0.04480731,0.02383608,0.3080536,0.6121431],"study_design_scores_gemma":[0.0002291295,0.0005959194,0.0039191,0.0001738259,0.0001703228,0.001713683,0.0001739978,0.02317791,0.02584473,0.005577125,0.9382576,0.0001667137],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04327248,0.006438639,0.3923124,0.001657125,0.00142297,0.0008537358,0.006079371,0.2968224,0.2511408],"genre_scores_gemma":[0.3208818,0.005520527,0.3697989,0.002312428,0.0008378527,0.0009641334,0.01685962,0.01588935,0.2669353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05919057,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04741470383063509,"score_gpt":0.2919412668482792,"score_spread":0.2445265630176441,"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."}}