{"id":"W1973618798","doi":"10.1145/985921.985927","title":"Eye contact sensing glasses for attention-sensitive wearable video blogging","year":2004,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Wearable computer; Eye contact; Computer science; Computer vision; Psychology; Communication","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":[0.0003507185,0.0004836153,0.0002598535,0.0004869405,0.0005175363,0.0007944418,0.0008133345,0.00101714,0.008761371],"category_scores_gemma":[0.001497092,0.000297352,0.0002932811,0.0002722527,0.0002326525,0.0007399003,0.0006038271,0.0003789502,0.001303351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000375897,"about_ca_system_score_gemma":0.0002477981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001741107,"about_ca_topic_score_gemma":0.00499639,"domain_scores_codex":[0.9996796,0.00007493496,0.00001815717,0.00007194703,0.0001178257,0.00003761163],"domain_scores_gemma":[0.9993468,0.0003162371,0.0000669418,0.00006768208,0.0001392409,0.0000631122],"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":[0.001853703,0.0003930562,0.007312002,0.001108058,0.00009647315,0.0009901476,0.0007538036,0.00075644,0.4687107,0.00190442,0.03247451,0.4836466],"study_design_scores_gemma":[0.0006143555,0.005192021,0.07313678,0.0006951243,0.0008141982,0.008339703,0.001670879,0.06937816,0.6190905,0.005559404,0.2150432,0.0004657561],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.420408,0.01460708,0.49366,0.003444596,0.002679714,0.001625693,0.001659172,0.01182147,0.05009425],"genre_scores_gemma":[0.8058864,0.002031307,0.1695136,0.001197681,0.0004907816,0.0005306508,0.0003722608,0.0002413428,0.01973595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008761371,"threshold_uncertainty_score":0.02930975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500867611168374,"score_gpt":0.2606398419496803,"score_spread":0.2456311658379965,"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."}}