{"id":"W373080653","doi":"10.1007/978-3-319-06284-6_2","title":"Cognitive Cellular Network Management","year":2014,"lang":"en","type":"book-chapter","venue":"Springer briefs in electrical and computer engineering","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Heterogeneous network; Backhaul (telecommunications); Cognitive radio; Cognitive network; Computer science; Computer network; Software deployment; Cellular network; Cognition; Wireless network; Wireless; Radio resource management; Telecommunications; Psychology; Neuroscience; Software 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002883185,0.0006567639,0.0003325456,0.0006308616,0.0003813988,0.001553205,0.000842365,0.0007702986,0.01190718],"category_scores_gemma":[0.0007025549,0.0001561818,0.0001858641,0.0007068123,0.0004173997,0.001138442,0.0008887813,0.0008715646,0.004420451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008081864,"about_ca_system_score_gemma":0.0007798768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001084793,"about_ca_topic_score_gemma":0.001525767,"domain_scores_codex":[0.9997991,0.0000243253,0.000007988378,0.00003801727,0.0001014689,0.00002922749],"domain_scores_gemma":[0.9998196,0.00004142182,0.00001202426,0.00003346747,0.00006827572,0.00002519633],"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":[0.00003256601,0.00005835115,0.0001378209,0.0001388253,0.00001443357,0.0001025799,0.00005689777,0.008705813,0.002629814,0.1117347,0.1127517,0.7636366],"study_design_scores_gemma":[0.00001202677,0.00007074635,0.0006173664,0.0001906957,0.00002608123,0.00052594,0.00008640713,0.0484065,0.002657764,0.1681148,0.7792594,0.00003227931],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00841306,0.0788672,0.3455801,0.009311964,0.01267362,0.0001568379,0.0003281768,0.001685697,0.5429835],"genre_scores_gemma":[0.2602692,0.07510575,0.05049574,0.003231086,0.01086877,0.0002256881,0.0007952884,0.0002509651,0.5987575],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01190718,"threshold_uncertainty_score":0.03983355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005681127367985719,"score_gpt":0.1747466500539067,"score_spread":0.169065522685921,"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."}}