{"id":"W2006548718","doi":"10.1109/vtcfall.2013.6692380","title":"Properties of Blind Rendezvous in Channel Hopping Cognitive Piconets","year":2013,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Rendezvous; Piconet; Computer science; Cognitive radio; Channel (broadcasting); Probabilistic logic; Computer network; Cognition; Transmission (telecommunications); Focus (optics); Protocol (science); Cognitive network; Wireless; Telecommunications; Artificial intelligence; Bluetooth; Engineering; Psychology","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":[0.002857026,0.0005605972,0.001170939,0.001887455,0.001661637,0.002593503,0.001431785,0.001142835,0.002355547],"category_scores_gemma":[0.03323453,0.0005740785,0.0005624766,0.0009106525,0.005256146,0.002570598,0.002782651,0.001277035,0.0003322667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149559,"about_ca_system_score_gemma":0.001338948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001876374,"about_ca_topic_score_gemma":0.0007142805,"domain_scores_codex":[0.9980649,0.0004391464,0.000116589,0.0002933576,0.0006539351,0.000432106],"domain_scores_gemma":[0.9664129,0.02266721,0.004636616,0.002744462,0.002038902,0.001499878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001212914,0.0001595985,0.005866131,0.0003011137,0.0001383802,0.0007780346,0.00177206,0.3790312,0.03172733,0.5616333,0.001692171,0.01568779],"study_design_scores_gemma":[0.0001088743,0.0002208238,0.002098311,0.00005508148,0.0000431826,0.0006737563,0.000376461,0.784525,0.00627446,0.2045827,0.0009453931,0.00009597836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5946584,0.0006443615,0.3812194,0.0004991078,0.00007850664,0.0001545915,0.0003074848,0.0005449046,0.02189334],"genre_scores_gemma":[0.9944382,0.0001452836,0.004523045,0.00004053334,0.00002266445,0.0000558323,0.00005044952,0.0000465389,0.0006774678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002857026,"threshold_uncertainty_score":0.0151096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03115083393447735,"score_gpt":0.2250042575680565,"score_spread":0.1938534236335791,"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."}}