{"id":"W2034230250","doi":"10.1109/twc.2012.032712.110197","title":"Interference Analysis and Mitigation for Cognitive-Empowered Femtocells Through Stochastic Dual Control","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cognitive radio; Computer science; Interference (communication); Femtocell; Dual (grammatical number); Stochastic geometry; Control (management); Stochastic process; Computer network; Distributed computing; Wireless; Telecommunications; Channel (broadcasting); Mathematics; Artificial intelligence; Base station","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002556031,0.0001994884,0.0002997749,0.0002369014,0.0007349486,0.0001531619,0.0004289031,0.00008495284,0.000009468547],"category_scores_gemma":[0.00001413158,0.0002095882,0.0001776969,0.0008216029,0.0002182658,0.0006766952,0.00001072833,0.0002771005,0.000009799158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005812657,"about_ca_system_score_gemma":0.00003937302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004982611,"about_ca_topic_score_gemma":0.0002230843,"domain_scores_codex":[0.9986683,0.0002060763,0.000316827,0.0003055344,0.0001497447,0.0003535558],"domain_scores_gemma":[0.99692,0.001768212,0.0001353339,0.0008338642,0.0002104007,0.0001321507],"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":[0.0005779132,0.005201512,0.001379293,0.0001134103,0.007608548,0.000003760786,0.03000234,0.02255354,0.01228147,0.105873,0.000181058,0.8142241],"study_design_scores_gemma":[0.001808122,0.0002073002,0.002713561,0.0001296899,0.001130777,0.00002298693,0.0004360097,0.9874623,0.00440164,0.001069808,0.00008645312,0.0005313616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02467092,0.0002797413,0.9729227,0.0009741916,0.0001983243,0.0005412075,0.00009278284,0.0001280002,0.0001921547],"genre_scores_gemma":[0.9867551,0.0001596108,0.01254068,0.0002672898,0.00003744664,0.0001631128,0.00001973428,0.00001577434,0.00004127655],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9649087,"threshold_uncertainty_score":0.8546759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02974183083733808,"score_gpt":0.2858407643431212,"score_spread":0.2560989335057832,"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."}}