{"id":"W1516893568","doi":"","title":"Transparent Gaze Communications for Multiparty Videoconference System","year":2004,"lang":"en","type":"article","venue":"IEICE Transactions on Information and Systems","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Computer science; Gaze; Videoconferencing; Multimedia; Artificial intelligence","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":[0.000481908,0.0003671238,0.0003515626,0.000589381,0.001258053,0.0006833503,0.0005342835,0.0009298584,0.008211029],"category_scores_gemma":[0.001355805,0.0002591027,0.0002606589,0.0003102045,0.0003127664,0.001100341,0.001203843,0.0007580709,0.0008648707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007840665,"about_ca_system_score_gemma":0.0006714192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004326356,"about_ca_topic_score_gemma":0.007590186,"domain_scores_codex":[0.9994168,0.0001272911,0.00002026341,0.00008469757,0.0002199431,0.0001309679],"domain_scores_gemma":[0.9992318,0.0001968847,0.00005598119,0.0001756793,0.0002894785,0.00005013314],"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":[0.002459819,0.0002693596,0.004379431,0.0002786103,0.0001417944,0.001206026,0.001336184,0.01435682,0.6292162,0.03210714,0.02900219,0.2852465],"study_design_scores_gemma":[0.0002847808,0.0007531005,0.007076905,0.00008270303,0.0002015683,0.001007635,0.0004288127,0.6525706,0.2940072,0.01467809,0.02874641,0.0001621566],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3630318,0.001784009,0.5974153,0.001460114,0.0005403374,0.0002460056,0.0005164478,0.005687282,0.02931863],"genre_scores_gemma":[0.9508054,0.0003133577,0.03654588,0.0001589829,0.0001329619,0.0000913223,0.0001295824,0.00008008629,0.01174242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008211029,"threshold_uncertainty_score":0.02746856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03158853536043122,"score_gpt":0.2424071981491574,"score_spread":0.2108186627887262,"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."}}