{"id":"W2013399540","doi":"10.1145/1095034.1095043","title":"ViewPointer","year":2005,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Headset; Computer vision; Wearable computer; Context (archaeology); Artificial intelligence; Bluetooth; Object (grammar); Mobile device; Wireless; Embedded system","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":[0.0003070122,0.0006960857,0.0004027992,0.0003606437,0.0002587422,0.00102652,0.001070161,0.0007896748,0.01878735],"category_scores_gemma":[0.001208214,0.0002955404,0.0003658011,0.0002172422,0.0003499406,0.00146265,0.001292828,0.0007193808,0.006619057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000292881,"about_ca_system_score_gemma":0.0004293321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241749,"about_ca_topic_score_gemma":0.002417827,"domain_scores_codex":[0.9995382,0.00005374042,0.00001709669,0.0001231435,0.0002224759,0.00004551471],"domain_scores_gemma":[0.9995524,0.00008042496,0.00003828232,0.0001379775,0.0001270017,0.00006388209],"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":[0.0005219108,0.0001509741,0.003838527,0.0007433277,0.00004926585,0.0009778693,0.0007788576,0.002793829,0.1834065,0.05331026,0.04980968,0.7036189],"study_design_scores_gemma":[0.00008799607,0.0008403181,0.003900026,0.0001648061,0.00007854655,0.003592312,0.000236541,0.03351224,0.1025828,0.009443222,0.8454491,0.000112039],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03507755,0.003750107,0.8173617,0.001078024,0.001181609,0.0004480376,0.001219778,0.01914736,0.1207358],"genre_scores_gemma":[0.2956582,0.003812765,0.4945623,0.001936976,0.0004161646,0.0003762169,0.002457421,0.001804872,0.198975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01878735,"threshold_uncertainty_score":0.06284994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009146022645638971,"score_gpt":0.2320200081583207,"score_spread":0.2228739855126817,"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."}}