{"id":"W2104417207","doi":"10.1504/ijaacs.2009.024281","title":"Differential sensing in cognitive personal area networks with bursty secondary traffic and varying primary activity factor","year":2009,"lang":"en","type":"article","venue":"International Journal of Autonomous and Adaptive Communications Systems","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Cognitive radio; Channel (broadcasting); Idle; Probabilistic logic; Set (abstract data type); Transmission (telecommunications); Computer network; Differential (mechanical device); Real-time computing; Telecommunications; Wireless; Artificial intelligence","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":[0.002953614,0.0005239369,0.0008086262,0.0006710338,0.0005738455,0.0009561453,0.001371984,0.0007443236,0.0002816555],"category_scores_gemma":[0.01148994,0.0006499741,0.0003059621,0.0006674315,0.001680258,0.001336804,0.001152047,0.0005065002,0.00005626523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001208092,"about_ca_system_score_gemma":0.0006449626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002912782,"about_ca_topic_score_gemma":0.002163186,"domain_scores_codex":[0.9987024,0.0004003225,0.00005382905,0.0002221782,0.0003584067,0.0002629313],"domain_scores_gemma":[0.9906026,0.007415086,0.000892107,0.0003785926,0.0004965622,0.0002149807],"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":[0.0004167713,0.00009719168,0.00721539,0.0001353071,0.00008266159,0.0009797569,0.000427662,0.9285815,0.01005636,0.02776231,0.0003354002,0.02390977],"study_design_scores_gemma":[0.00001208675,0.00004997175,0.001118194,0.000004816002,0.0000141746,0.0001677037,0.00004981511,0.9878522,0.0006583759,0.009964101,0.00009698748,0.00001156368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5133387,0.0008344344,0.4826759,0.0003409489,0.00004087551,0.00004950429,0.00004994064,0.0001436672,0.002525991],"genre_scores_gemma":[0.9956286,0.0001121206,0.00400404,0.00001724006,0.00001239731,0.00001448177,0.000007248826,0.00000331439,0.0002005899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002953614,"threshold_uncertainty_score":0.01562041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02714402896198772,"score_gpt":0.2539145155949036,"score_spread":0.2267704866329159,"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."}}