{"id":"W1689783228","doi":"10.1002/wcm.1232","title":"Performance of simple cognitive personal area networks with finite buffers and adaptive superframe duration","year":2011,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Superframe; Computer science; Piconet; Network packet; Duration (music); Computer network; Duty cycle; Personal area network; Simple (philosophy); Real-time computing; Bandwidth (computing); Node (physics); Transmission (telecommunications); Network performance; Channel (broadcasting); Wireless; Telecommunications; Bluetooth; Voltage; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002904353,0.001241709,0.001138718,0.0008296327,0.0008064301,0.001362899,0.001568479,0.00132392,0.0008006201],"category_scores_gemma":[0.008641106,0.0003918703,0.0003881525,0.0006421033,0.001955645,0.001497813,0.001238914,0.0005991937,0.0001093628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001897084,"about_ca_system_score_gemma":0.001055775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006393817,"about_ca_topic_score_gemma":0.003686351,"domain_scores_codex":[0.9986159,0.0004124579,0.00005553587,0.0002255709,0.0002612956,0.0004292268],"domain_scores_gemma":[0.9909258,0.005980673,0.001022507,0.0004659996,0.0009712891,0.000633735],"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":[0.0018849,0.0002445426,0.00268466,0.0001195073,0.0001287199,0.0002442375,0.0001329384,0.9727049,0.01260408,0.002672118,0.0002204741,0.006358866],"study_design_scores_gemma":[0.00008562367,0.0005051769,0.0007888554,0.000009318721,0.00004797889,0.00006600351,0.00004336595,0.9936161,0.003412002,0.001353206,0.00004887552,0.00002345008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702323,0.0004293103,0.02756021,0.0001131762,0.00004805214,0.00003948133,0.00004359778,0.0001137501,0.00142014],"genre_scores_gemma":[0.9987572,0.00004869248,0.001002448,0.0000156379,0.000006988168,0.000008883352,0.000007221805,0.000003194112,0.0001496259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006393817,"threshold_uncertainty_score":0.01535988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02771401659211796,"score_gpt":0.2284523776219335,"score_spread":0.2007383610298156,"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."}}