{"id":"W2016739648","doi":"10.1109/glocom.2006.792","title":"WLC30-6: Admission Control in Power Constrained OFDM/TDMA Wireless Mesh Networks","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Wireless mesh network; Router; Computer network; Network packet; Sleep mode; Mesh networking; Switched mesh; Markov decision process; Time division multiple access; Shared mesh; Markov process; Power (physics); Wireless; Wireless network; Power consumption; Telecommunications","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":[0.001782578,0.0005915784,0.0007075173,0.0004344714,0.0004907234,0.0009798598,0.0007919631,0.0006778815,0.001183629],"category_scores_gemma":[0.004152801,0.0001956795,0.0003233258,0.0005346763,0.0009154799,0.0007720591,0.0007728279,0.0006681787,0.00008298778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001351377,"about_ca_system_score_gemma":0.001350652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006723588,"about_ca_topic_score_gemma":0.00305773,"domain_scores_codex":[0.9991391,0.0003290494,0.00002822525,0.00007417877,0.0002203482,0.0002091547],"domain_scores_gemma":[0.9982444,0.001177393,0.0002072616,0.0000598828,0.0001941574,0.0001168841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001207553,0.00007602956,0.000628443,0.00004308993,0.00002366395,0.00007185323,0.00004072927,0.9646466,0.003052251,0.01487338,0.000443408,0.01597978],"study_design_scores_gemma":[0.000005122026,0.00001641343,0.00004388593,0.000001225951,0.000002426246,0.000004492967,0.000003805833,0.9982293,0.0002873092,0.001353273,0.00005079998,0.000001824314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2199546,0.0006840992,0.7710233,0.0007196489,0.00009698357,0.0001573426,0.00006054687,0.0002076609,0.007095697],"genre_scores_gemma":[0.9859272,0.0001489418,0.01293448,0.00003626822,0.00003068746,0.00004474754,0.00001285137,0.000009572527,0.0008553038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006723588,"threshold_uncertainty_score":0.0133689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002707240748214062,"score_gpt":0.1876594372630568,"score_spread":0.1849521965148427,"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."}}