{"id":"W2306198165","doi":"","title":"Optimal Sensing Order in Cognitive Radio Networks with Channel Stability and Traffic Differentiation","year":2013,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Cognitive radio; Reconfigurability; Channel (broadcasting); Computer science; Stability (learning theory); Dynamic programming; Computer network; Channel allocation schemes; Quality (philosophy); Function (biology); Order (exchange); Mathematical optimization; Telecommunications; Machine learning; Algorithm; Mathematics; 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":[0.002462264,0.0009166595,0.001078542,0.0006853477,0.0004624596,0.001459136,0.001282318,0.0009866444,0.0008065992],"category_scores_gemma":[0.008112418,0.0006505161,0.0005942463,0.0007888963,0.00159327,0.001692618,0.0009712572,0.001382308,0.0001021493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002275657,"about_ca_system_score_gemma":0.001795503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00624212,"about_ca_topic_score_gemma":0.003910913,"domain_scores_codex":[0.9981781,0.0006433676,0.0000787048,0.0003527511,0.0003717509,0.0003753378],"domain_scores_gemma":[0.9943817,0.003900685,0.0007162197,0.0002118527,0.00043703,0.0003525259],"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":[0.0001160313,0.00005963415,0.0005118732,0.00003557432,0.00001994232,0.00009073537,0.00009659024,0.9648807,0.001269105,0.02647735,0.0001872402,0.006255235],"study_design_scores_gemma":[0.000008955943,0.00003524273,0.0001139808,0.000003780298,0.00000567372,0.00001400105,0.00001465682,0.9902241,0.000236078,0.00927255,0.00006431839,0.000006668365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2074061,0.0004715305,0.7877055,0.0005071125,0.00004605493,0.00007930343,0.000095382,0.0001183041,0.003570781],"genre_scores_gemma":[0.9807513,0.0001354701,0.01775879,0.00004720168,0.00001582161,0.00004080557,0.00002548434,0.00001379942,0.001211411],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00624212,"threshold_uncertainty_score":0.01651114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00938101076858537,"score_gpt":0.2044101327481745,"score_spread":0.1950291219795892,"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."}}