{"id":"W2901752692","doi":"10.2316/journal.206.2018.6.206-5160","title":"QUICK TWO-WAY TIME MESSAGE EXCHANGE FOR TIME SYNCHRONIZATION IN ROBOT NETWORKS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Network Time Synchronization Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Southwest University; Southwest University of Science and Technology; National Natural Science Foundation of China","keywords":"Synchronization (alternating current); Computer science; Time synchronization; Robot; Real-time computing; Computer network; Artificial intelligence; Channel (broadcasting)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009779534,0.0006393974,0.0005867452,0.0007796175,0.0007969452,0.000945797,0.0009812971,0.0005978027,0.004244645],"category_scores_gemma":[0.003238083,0.0002327616,0.000288879,0.001099564,0.0004951141,0.001643118,0.001181752,0.001068426,0.001041873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006245227,"about_ca_system_score_gemma":0.0009169377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008672708,"about_ca_topic_score_gemma":0.001135072,"domain_scores_codex":[0.9990699,0.0002746741,0.00008258412,0.0001758491,0.0002999287,0.00009724479],"domain_scores_gemma":[0.9988292,0.0004167954,0.0001877962,0.0002587916,0.0002475362,0.00005992742],"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":[0.0008936023,0.0001099099,0.00118332,0.0008813249,0.00009562015,0.0004266729,0.0005506406,0.1093879,0.1083011,0.2124403,0.01598617,0.5497434],"study_design_scores_gemma":[0.0002334657,0.0006963721,0.0009822799,0.0001524075,0.0001293988,0.000720033,0.000160203,0.7094148,0.09287219,0.0594715,0.135049,0.0001183113],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005263876,0.0009261206,0.9902551,0.000111897,0.0002265451,0.0000902996,0.00005558653,0.000896454,0.002174121],"genre_scores_gemma":[0.5014246,0.001940971,0.4846712,0.0003361843,0.0003773468,0.0007095067,0.0005156021,0.0003015146,0.009723101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004244645,"threshold_uncertainty_score":0.01419979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007484217637689139,"score_gpt":0.2498458327435494,"score_spread":0.2423616151058602,"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."}}