{"id":"W2070943779","doi":"10.1109/jcn.2014.000009","title":"An opportunistic channel access scheme for interweave cognitive radio systems","year":2014,"lang":"en","type":"article","venue":"Journal of Communications and Networks","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Cognitive radio; Channel (broadcasting); Idle; Throughput; Computer network; Cognition; Scheme (mathematics); Telecommunications; Wireless; Mathematics","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":[0.001063247,0.0001252852,0.0003009675,0.0001311538,0.0003427105,0.0005543686,0.00122567,0.00006810666,8.726931e-7],"category_scores_gemma":[0.00006760971,0.00010914,0.00008338915,0.0001939268,0.0001087808,0.0006890202,0.0002460245,0.0002988971,2.46407e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002565562,"about_ca_system_score_gemma":0.00004834287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006791448,"about_ca_topic_score_gemma":0.00001229392,"domain_scores_codex":[0.9988356,0.000248463,0.0004430738,0.0001451789,0.0001192402,0.000208492],"domain_scores_gemma":[0.9972618,0.0009744335,0.0004736854,0.0005904266,0.0005121912,0.0001874867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002233788,0.00064551,0.0007845297,0.00007193637,0.0005313878,0.000029053,0.00143749,0.004888116,0.0001657878,0.2145473,0.001920977,0.7747546],"study_design_scores_gemma":[0.0005556868,0.0004112557,0.000433416,0.0002906639,0.00004029928,0.0002963151,0.000123792,0.9925326,0.000003881994,0.002030119,0.003144736,0.0001373066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00303075,0.003027675,0.9920455,0.0008192993,0.0003534691,0.0001775394,0.000003263686,0.00002092759,0.0005215837],"genre_scores_gemma":[0.9874303,0.002154177,0.009687719,0.0002297174,0.0004533825,0.000007780584,0.000009992271,0.00001212421,0.00001477798],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9876444,"threshold_uncertainty_score":0.5345789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05070808993274047,"score_gpt":0.3213247911527626,"score_spread":0.2706167012200222,"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."}}