{"id":"W4251102826","doi":"10.1109/glocom.2014.7417239","title":"Prioritized Access in a Channel-Hopping Cognitive Network with Spectrum Sensing","year":2014,"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; Channel (broadcasting); Network packet; Bandwidth (computing); Transmission (telecommunications); Node (physics); Bandwidth allocation; Cognitive network; Channel allocation schemes; Telecommunications; Wireless; 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"],"consensus_categories":[],"category_scores_codex":[0.0009089102,0.0004380415,0.0006174786,0.0001583777,0.000626487,0.001027957,0.0027478,0.0001526892,0.0000123098],"category_scores_gemma":[0.0001290593,0.0004374607,0.000102678,0.001936209,0.0003588398,0.00106634,0.00116172,0.0006238758,0.0000508772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003116194,"about_ca_system_score_gemma":0.0003744151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00083942,"about_ca_topic_score_gemma":0.01289169,"domain_scores_codex":[0.9964208,0.000805909,0.0005878701,0.0007733441,0.0004147041,0.0009973482],"domain_scores_gemma":[0.9962425,0.0006308024,0.0003452382,0.002063509,0.0004612844,0.0002566893],"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":[0.0004675364,0.0009038814,0.02540599,0.0001026029,0.0004747667,0.0001818313,0.002438311,0.007567583,0.00009839724,0.476175,0.004089841,0.4820942],"study_design_scores_gemma":[0.002291432,0.0001668757,0.01994152,0.00131299,0.00005273822,0.00020401,0.0002183315,0.9359069,0.00005773796,0.03696179,0.001887779,0.00099787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02290925,0.0005476294,0.9245444,0.006572502,0.0004575273,0.0007219844,0.00001461849,0.0003816346,0.04385046],"genre_scores_gemma":[0.9800114,0.0003612959,0.01850549,0.0008240189,0.0002022426,0.00001756826,0.00002650205,0.00002184203,0.00002965335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9571021,"threshold_uncertainty_score":0.9998077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04252013103595344,"score_gpt":0.3094440834311453,"score_spread":0.2669239523951919,"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."}}