{"id":"W2068152044","doi":"10.1145/1344471.1344486","title":"3D point-of-gaze estimation on a volumetric display","year":2008,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gaze; Computer science; Computer vision; Artificial intelligence; Vergence (optics); Eye tracking; Point (geometry); Tracking (education); Computer graphics (images); Mathematics; Psychology","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":[0.0003143741,0.0005839362,0.0006797062,0.001452357,0.0001610034,0.0006812931,0.0005366159,0.0005918849,0.002953356],"category_scores_gemma":[0.001969844,0.0003205689,0.0004741243,0.000677755,0.0001477779,0.0005614688,0.0008956413,0.0003527042,0.0009014935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002366693,"about_ca_system_score_gemma":0.0002979175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00447516,"about_ca_topic_score_gemma":0.004323543,"domain_scores_codex":[0.9995928,0.00007252349,0.00002050639,0.00007033965,0.0002100827,0.00003369206],"domain_scores_gemma":[0.9990959,0.0003012293,0.0001007675,0.00008426848,0.0003668693,0.00005099262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007597335,0.0001021589,0.01094051,0.0004891619,0.0001665112,0.0004225937,0.0005602298,0.02976171,0.7059248,0.001174781,0.004584498,0.2451133],"study_design_scores_gemma":[0.0001099786,0.0006649495,0.08337547,0.0001196646,0.0001472476,0.00146783,0.0002665712,0.6065705,0.2983887,0.001313454,0.00731432,0.0002612064],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1878623,0.0004531234,0.7999235,0.0001361128,0.0000505188,0.0001453737,0.002038748,0.0065033,0.002887091],"genre_scores_gemma":[0.7741687,0.0005669102,0.2216754,0.00006426535,0.0000363671,0.0001469299,0.001024026,0.000280341,0.002037063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00447516,"threshold_uncertainty_score":0.009879947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01863287748665232,"score_gpt":0.2414519955085012,"score_spread":0.2228191180218488,"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."}}