{"id":"W2145239700","doi":"10.1109/robot.1998.680629","title":"Predictive windows for delay compensation in telepresence applications","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Compensation (psychology); Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000666104,0.00004996007,0.00005824286,0.00006857371,0.00006536031,0.00003612444,0.000291685,0.00001552426,0.00002468199],"category_scores_gemma":[0.00002358093,0.00004566392,0.00001862596,0.0002620265,0.0000182032,0.0005050853,0.00005850703,0.00004719408,0.00004419583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002411178,"about_ca_system_score_gemma":0.000005616915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004265658,"about_ca_topic_score_gemma":0.000004934659,"domain_scores_codex":[0.9994389,0.00001167602,0.0001194447,0.0002157331,0.00008638999,0.0001278585],"domain_scores_gemma":[0.9995412,0.0001102008,0.00003050087,0.000232038,0.00005117664,0.00003489868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005080382,0.0001785675,0.002647184,0.000009211189,0.000004480406,0.000001568416,0.0009259623,0.005018718,0.001202136,0.1720242,0.003116759,0.8148661],"study_design_scores_gemma":[0.0002481157,0.00002012481,0.00139666,0.000004579876,4.921503e-7,0.000002663825,0.00002697013,0.9759112,0.0005122256,0.006959686,0.01485639,0.00006088793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000109465,0.00004419473,0.9891981,0.0008716945,0.00003385024,0.0004469191,0.000001166413,0.00009390842,0.009200684],"genre_scores_gemma":[0.6253755,0.00001181609,0.3733376,0.0004387301,0.00002366917,0.0002144819,0.000001388386,0.000003402276,0.0005934315],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9708925,"threshold_uncertainty_score":0.1862121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02541586522250758,"score_gpt":0.2827734760275245,"score_spread":0.257357610805017,"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."}}