{"id":"W1993555200","doi":"10.1109/glocom.2008.ecp.938","title":"Tradeoff Between CPAN Size and the Number of Working Channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Piconet; Channel (broadcasting); Computer science; Dependency (UML); Cognitive radio; Computer network; Telecommunications; Artificial intelligence; Bluetooth; Wireless","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":[0.003855829,0.0005921239,0.0008410841,0.0005761712,0.0007536038,0.001478791,0.002366374,0.0009723906,0.003016003],"category_scores_gemma":[0.02360183,0.0004411455,0.0002650316,0.0006602851,0.0007522706,0.003873523,0.001466886,0.0009669141,0.0005579537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006123789,"about_ca_system_score_gemma":0.001253649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009708552,"about_ca_topic_score_gemma":0.001051202,"domain_scores_codex":[0.9975188,0.0008730621,0.0001522477,0.0004685059,0.0005992507,0.000388299],"domain_scores_gemma":[0.9554681,0.03474067,0.001684506,0.003676603,0.003067154,0.001362992],"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":[0.005191476,0.001360799,0.01404192,0.0007715421,0.0002402879,0.00197299,0.0005747742,0.4334191,0.1202286,0.04168429,0.01123013,0.3692841],"study_design_scores_gemma":[0.0003175364,0.002278034,0.01269429,0.0001132125,0.0002047661,0.004816771,0.0005218477,0.8489503,0.08540591,0.03433444,0.01024277,0.0001200646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6108422,0.002552184,0.3437332,0.004137353,0.0003763359,0.0003722867,0.000696174,0.001380555,0.03590969],"genre_scores_gemma":[0.9523965,0.0006355139,0.04307056,0.0002814525,0.0001176595,0.000218159,0.0002041796,0.00009378328,0.002982373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003855829,"threshold_uncertainty_score":0.02039182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430507660304503,"score_gpt":0.2389247812759371,"score_spread":0.204619704672892,"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."}}