{"id":"W2290906325","doi":"10.1109/glocom.2015.7417239","title":"Prioritized Access in a Channel-Hopping Cognitive Network with Spectrum Sensing","year":2015,"lang":"en","type":"article","venue":"2015 IEEE Global Communications Conference (GLOBECOM)","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer network; Computer science; Cognitive radio; Network packet; Channel (broadcasting); Transmission (telecommunications); Node (physics); Bandwidth (computing); Bandwidth allocation; Channel allocation schemes; Wireless; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009457219,0.0004445951,0.000613722,0.0001675951,0.0004416672,0.001069284,0.002776597,0.0001574886,0.000007664584],"category_scores_gemma":[0.000139078,0.0004434574,0.00009215755,0.002305653,0.0003673331,0.001363421,0.001356863,0.0006317981,0.00005942497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005435871,"about_ca_system_score_gemma":0.0009457899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264917,"about_ca_topic_score_gemma":0.01418139,"domain_scores_codex":[0.9964387,0.0006796546,0.0006008892,0.0007525103,0.0005199342,0.001008286],"domain_scores_gemma":[0.9961659,0.0003731772,0.0003408485,0.00195858,0.0007470018,0.0004145284],"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":[0.001619918,0.002264224,0.06108218,0.0001430673,0.001120234,0.001266413,0.01051581,0.0207138,0.00008618631,0.4423634,0.02284745,0.4359773],"study_design_scores_gemma":[0.004649566,0.0002828902,0.01325414,0.001665233,0.00008145996,0.0005121835,0.001111334,0.9203531,0.00006561384,0.05408271,0.002429385,0.001512375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03466352,0.001789263,0.8921866,0.009982924,0.0008073935,0.001157265,0.00003035195,0.0005522522,0.05883037],"genre_scores_gemma":[0.9795018,0.0003463354,0.01920795,0.0006458734,0.0001864007,0.00001914733,0.00003178712,0.00002216174,0.00003851871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9448383,"threshold_uncertainty_score":0.9999677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08780904613142254,"score_gpt":0.3341840749583336,"score_spread":0.246375028826911,"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."}}