{"id":"W1968732129","doi":"10.1109/glocom.2006.748","title":"WLC23-4: Performance Enhancement of Medium Access Control for UWB WPAN","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of Waterloo","funders":"","keywords":"Computer science; Scheduling (production processes); Computer network; Personal area network; Distributed computing; Wireless; Schedule; Access control; Wireless network; Computation; Power control; Network topology; Heuristic; Power (physics); Engineering; Telecommunications; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007777767,0.00009266745,0.0001613954,0.00006559463,0.00004212682,0.00001142231,0.0005050726,0.00007005463,0.00004896548],"category_scores_gemma":[0.00001148527,0.0000940702,0.00004162564,0.0001157089,0.00004133053,0.0000951684,0.00003480445,0.00007575172,0.00001386204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004618294,"about_ca_system_score_gemma":0.00001326259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004669937,"about_ca_topic_score_gemma":0.00007510843,"domain_scores_codex":[0.9994075,0.000006600778,0.0002425599,0.00008606556,0.00006875953,0.0001885027],"domain_scores_gemma":[0.9993928,0.00006192437,0.00004389313,0.0004367838,0.00004770336,0.00001689643],"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":[0.000261528,0.001249063,0.1202673,0.001803569,0.0008282281,0.000002720979,0.0005461127,0.04807622,0.3635907,0.03659917,0.1422172,0.2845581],"study_design_scores_gemma":[0.002922557,0.0002045657,0.03549731,0.00007865418,0.00008657917,0.000006273278,0.00003616243,0.06170086,0.7150788,0.004810099,0.1790596,0.0005185133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8801938,0.0008518209,0.105111,0.0006273935,0.0002980759,0.0004865614,0.00003417377,0.0003760135,0.01202108],"genre_scores_gemma":[0.9973179,0.00009248274,0.002177009,0.00003413057,0.00003395864,0.0001722144,0.00002237703,0.0000144388,0.0001355347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3514881,"threshold_uncertainty_score":0.3836071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008378572416027385,"score_gpt":0.2292202724146186,"score_spread":0.2208416999985912,"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."}}