{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008051827,0.0003954781,0.0003865214,0.0004389809,0.0003855796,0.0005444016,0.0005816862,0.0004316908,0.001426188],"category_scores_gemma":[0.002310936,0.00007981826,0.0001804234,0.0004047571,0.000260345,0.0004221737,0.0003706302,0.0004668623,0.000365413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004038069,"about_ca_system_score_gemma":0.0005836441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001341994,"about_ca_topic_score_gemma":0.001394012,"domain_scores_codex":[0.9995428,0.000114955,0.00002208013,0.00004905105,0.0001794387,0.00009168286],"domain_scores_gemma":[0.9992515,0.000320093,0.00007166216,0.00009950178,0.0002202879,0.00003692293],"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":[0.0009624872,0.0003571192,0.001955853,0.0002289603,0.00007927408,0.0002859527,0.0001079846,0.2870627,0.1547775,0.01584473,0.004161625,0.5341758],"study_design_scores_gemma":[0.00005205601,0.0003496744,0.0006849195,0.000008916128,0.00002270566,0.0001267667,0.00001664077,0.9578605,0.03417444,0.002153991,0.004528652,0.00002076964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2461053,0.002345415,0.7282282,0.0004468337,0.0003726652,0.0001354773,0.00007561383,0.002691698,0.01959882],"genre_scores_gemma":[0.9328068,0.0003321891,0.06504948,0.00007126109,0.0000686115,0.0000512927,0.00006995306,0.00005231259,0.001498095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001426188,"threshold_uncertainty_score":0.004771054,"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."}}