{"id":"W2062007216","doi":"10.1049/iet-com.2014.0205","title":"Reliability‐based decision fusion scheme for cooperative spectrum sensing","year":2014,"lang":"en","type":"article","venue":"IET Communications","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Reliability (semiconductor); Computer science; Spectrum (functional analysis); Fusion; Scheme (mathematics); Reliability engineering; Sensor fusion; Artificial intelligence; Mathematics; Physics; Engineering","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":[0.002547818,0.0009566097,0.001022846,0.0005230119,0.0004539129,0.0007917768,0.001643758,0.0009380789,0.0009100171],"category_scores_gemma":[0.003761081,0.0003797422,0.0006844283,0.0006200369,0.0007926762,0.001313724,0.00138626,0.001240715,0.0002887311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007094398,"about_ca_system_score_gemma":0.000901476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001049698,"about_ca_topic_score_gemma":0.0007489698,"domain_scores_codex":[0.9981993,0.0006475888,0.0001009871,0.0003110412,0.0005514796,0.0001896375],"domain_scores_gemma":[0.9983278,0.0008808413,0.0002094203,0.0001777815,0.0003494141,0.00005467223],"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":[0.0005789232,0.0001379082,0.0005678658,0.0003217324,0.0001936259,0.0003350636,0.0004749318,0.6733508,0.02581824,0.09433088,0.002282914,0.2016071],"study_design_scores_gemma":[0.00002776563,0.0001793848,0.0001250531,0.00001354481,0.00003206949,0.0001032771,0.00001944165,0.9810607,0.003347085,0.01385514,0.001211284,0.00002517357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0106443,0.0003173686,0.9874378,0.0001171612,0.00004311665,0.00003406997,0.00001500344,0.00008674315,0.001304525],"genre_scores_gemma":[0.8485415,0.0003694232,0.1487149,0.0001319053,0.00009315209,0.0001024058,0.00005108998,0.00002358,0.001971964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002547818,"threshold_uncertainty_score":0.01347429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02479238218581995,"score_gpt":0.2865946680952486,"score_spread":0.2618022859094287,"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."}}