{"id":"W2122520867","doi":"10.1109/glocom.2009.5425802","title":"Relay Based Cooperative Spectrum Sensing in Cognitive Radio Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cognitive radio; Relay; Rayleigh fading; Computer science; False alarm; Fading; Detector; Computer network; Cognitive network; Relay channel; Cognition; Wireless; Telecommunications; Electronic engineering; Engineering; Channel (broadcasting); Artificial intelligence; Power (physics); Psychology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004031905,0.0002746223,0.0003440052,0.000233658,0.0001850764,0.0002780162,0.000247538,0.0001095427,0.0000427961],"category_scores_gemma":[0.00006887176,0.0002556729,0.00009417513,0.001212329,0.00006259372,0.0004312187,0.00005217977,0.0004460201,0.00001775394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001336388,"about_ca_system_score_gemma":0.0001031249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004725473,"about_ca_topic_score_gemma":0.000279683,"domain_scores_codex":[0.9978926,0.0002042317,0.0003394679,0.0006602518,0.0002367223,0.0006666871],"domain_scores_gemma":[0.9989442,0.0004340342,0.00007975697,0.0002994018,0.00009704368,0.0001455372],"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":[0.0003012527,0.0005896027,0.002137324,0.000006725174,0.0000947319,0.003570496,0.002077654,0.1932078,0.0006809656,0.09273547,0.00323372,0.7013643],"study_design_scores_gemma":[0.001068658,0.0002361386,0.009699197,0.0001398011,0.000007169972,0.00006900164,0.00005334775,0.9859672,0.001236773,0.001033389,0.0001085234,0.0003808059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02217928,0.0002153133,0.9492345,0.003237987,0.0002418473,0.0002901951,5.875174e-7,0.0002376737,0.02436261],"genre_scores_gemma":[0.9811578,0.00002646853,0.01478131,0.003596481,0.0002123052,7.992594e-7,0.000005358604,0.00001204428,0.0002074472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9589785,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01348044062725041,"score_gpt":0.2425016647093538,"score_spread":0.2290212240821034,"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."}}