{"id":"W1983300637","doi":"10.5539/cis.v3n3p3","title":"Supporting Differentiated Service in Cognitive Radio Wireless Mesh Networks","year":2010,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computer network; Cognitive radio; Wireless mesh network; Wireless ad hoc network; Wireless network; Network packet; Throughput; Wireless; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009168162,0.0001111867,0.0001250552,0.0002881315,0.0003670325,0.0007536304,0.0009495487,0.00004268789,0.00001356792],"category_scores_gemma":[0.00004425887,0.0001010644,0.00001634016,0.001690844,0.0001526087,0.007354928,0.0007664692,0.0003030945,0.00001313618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001774298,"about_ca_system_score_gemma":0.00009625866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005741587,"about_ca_topic_score_gemma":0.00003140461,"domain_scores_codex":[0.9988595,0.00003708197,0.0003569496,0.000206655,0.0002374918,0.0003023488],"domain_scores_gemma":[0.9988973,0.000111648,0.0001418156,0.0003220976,0.000403975,0.0001231989],"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":[0.000006158827,0.00004016609,0.007920668,0.00001379445,0.000004787586,0.000001363241,0.008797513,0.0002539635,0.0008128635,0.1397042,0.0001631066,0.8422815],"study_design_scores_gemma":[0.0003273551,0.00001571078,0.07979207,0.0000313367,8.862269e-7,0.00001334935,0.00003911427,0.9189347,0.0002384074,0.00005875887,0.0004182602,0.0001300325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.342294,0.00001072329,0.6557078,0.0003734491,0.0003991727,0.0001338638,4.656059e-7,0.00007574791,0.001004701],"genre_scores_gemma":[0.9937911,0.00009235317,0.004218229,0.001840096,0.00003512398,0.000008801869,0.00000718663,0.000001899003,0.000005223846],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9186808,"threshold_uncertainty_score":0.7267276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212291027254848,"score_gpt":0.2862973900298375,"score_spread":0.264174479757289,"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."}}