{"id":"W4254395628","doi":"10.1002/wcm.732","title":"Dynamic spectrum management for cognitive radio: an overview","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Cognitive radio; Computer science; Scalability; Spectrum (functional analysis); Spectrum management; Mathematical optimization; Graph; Radio spectrum; Distributed computing; Theoretical computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006259209,0.0009328933,0.0006414342,0.001865741,0.0003931446,0.002296264,0.001200297,0.001822864,0.001824763],"category_scores_gemma":[0.0006327305,0.0005184564,0.0006247116,0.002506615,0.0007636979,0.002304828,0.0008299185,0.001415606,0.001016845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009418906,"about_ca_system_score_gemma":0.0006197149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001749144,"about_ca_topic_score_gemma":0.0009260235,"domain_scores_codex":[0.9995301,0.0001022687,0.00003937814,0.0001028069,0.0001848096,0.00004071017],"domain_scores_gemma":[0.9996548,0.000177842,0.00002807977,0.00002164335,0.00009001709,0.00002762079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001056112,0.0002736862,0.001014667,0.004380998,0.0001402617,0.0006245262,0.0001931867,0.04438145,0.003998064,0.1700659,0.01790744,0.7569142],"study_design_scores_gemma":[0.00004485965,0.000403084,0.002186048,0.002137616,0.0001637003,0.002491526,0.0002764307,0.1866741,0.003042244,0.1830635,0.6193733,0.0001436103],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004383294,0.6696526,0.2731613,0.002487312,0.001212271,0.00009829773,0.00007067774,0.0003395885,0.04859473],"genre_scores_gemma":[0.1488581,0.7028401,0.1285959,0.001632003,0.005196735,0.0002339284,0.0002197281,0.00007902785,0.01234444],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002296264,"threshold_uncertainty_score":0.006833911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02764892676940428,"score_gpt":0.3110238491633988,"score_spread":0.2833749223939945,"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."}}