{"id":"W2243735628","doi":"","title":"Queueing model for heterogeneous opportunistic spectrum access","year":2014,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","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":"Computer science; Queueing theory; Markov chain; Queue; Markov process; Layered queueing network; Service (business); Markov model; Computer network; Mathematical optimization; Real-time computing; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000287636,0.0002138443,0.0002574397,0.0001124129,0.0004693923,0.0004571326,0.0006931661,0.0001050687,0.000004864873],"category_scores_gemma":[0.00006962788,0.0002136177,0.0001481303,0.0001798897,0.00009664712,0.0003211992,0.0001280431,0.0001867155,0.000005447584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001080357,"about_ca_system_score_gemma":0.0000551854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002705882,"about_ca_topic_score_gemma":0.00007027431,"domain_scores_codex":[0.9984743,0.00005995676,0.0002414517,0.0005200803,0.0001873155,0.0005168956],"domain_scores_gemma":[0.9989743,0.0002462776,0.0001089274,0.0004376286,0.00005619948,0.000176702],"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":[0.000028465,0.00005436067,0.0001695596,0.00004093771,0.00005963537,0.00006950171,0.001036272,0.02799518,0.0002964181,0.8251115,0.0008805628,0.1442576],"study_design_scores_gemma":[0.0002886465,0.00005642666,0.00006681871,0.00001628086,0.00001324957,0.00006775279,0.000004454477,0.8981985,0.0003605984,0.0988464,0.001819095,0.0002617287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0299899,0.00006390217,0.9655849,0.001821098,0.000377602,0.0002155464,0.000004488651,0.0002217147,0.001720852],"genre_scores_gemma":[0.9630433,0.00003416141,0.03461102,0.001467112,0.000425583,0.00001369013,0.000007613541,0.0000283925,0.0003691067],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9330534,"threshold_uncertainty_score":0.8711078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02444472384777924,"score_gpt":0.2482026489398164,"score_spread":0.2237579250920372,"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."}}