{"id":"W2961510306","doi":"10.18280/ts.360115","title":"Spectrum Signals Handoff in LTE Cognitive Radio Networks Using Reinforcement Learning","year":2019,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Handover; Reinforcement learning; Cognitive radio; Computer science; Cognition; Computer network; Artificial intelligence; Telecommunications; Psychology; Neuroscience; Wireless","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001384921,0.0002415408,0.000324195,0.0003118394,0.000191114,0.0003041573,0.001073094,0.00008943055,0.0006296853],"category_scores_gemma":[0.00002110484,0.0002468112,0.00009805454,0.0008368202,0.00006670793,0.0006441474,0.0005895825,0.0006507278,0.0001118729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002465986,"about_ca_system_score_gemma":0.0001278871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006909751,"about_ca_topic_score_gemma":0.0000240059,"domain_scores_codex":[0.9969968,0.0004914561,0.000557253,0.0005017335,0.0007026417,0.000750183],"domain_scores_gemma":[0.9986004,0.0004809175,0.0002009037,0.0004804753,0.0001009519,0.0001363925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006798306,0.00008794432,0.009921435,0.00001461031,0.00004834017,0.0000186001,0.0006318844,0.9785378,0.001408716,0.003391733,0.00006814835,0.005802782],"study_design_scores_gemma":[0.001831641,0.0002224552,0.004115416,0.0002185331,0.000006150475,0.000007921502,0.00008800123,0.9917279,0.0009698169,0.0001020328,0.0004263145,0.0002838543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2241209,0.0003634397,0.7717962,0.0002662798,0.0001241351,0.0007977541,4.592306e-7,0.0001106245,0.002420249],"genre_scores_gemma":[0.9975605,0.0000787036,0.001605254,0.0002048473,0.0001247124,0.00004658733,0.00001414124,0.00002298818,0.0003422615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7734396,"threshold_uncertainty_score":0.9999984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02834464732100636,"score_gpt":0.2778013542339796,"score_spread":0.2494567069129732,"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."}}