{"id":"W2100627208","doi":"10.1186/1687-1499-2013-184","title":"A decoding-based fusion rule for cooperative spectrum sensing with nonorthogonal transmission of local decisions","year":2013,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cognitive radio; Fusion center; Decoding methods; Transmission (telecommunications); Energy (signal processing); Algorithm; Binary number; Fusion rules; Fusion; Keying; Telecommunications; Decision rule; Artificial intelligence; Wireless; Arithmetic; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00467012,0.0008765803,0.001597416,0.0007429513,0.0005795562,0.001989437,0.001832696,0.001588113,0.0007794827],"category_scores_gemma":[0.01493684,0.0003743714,0.0006462587,0.0008210365,0.001998774,0.001519398,0.001253293,0.001830874,0.0004917544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009001936,"about_ca_system_score_gemma":0.001244241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001743739,"about_ca_topic_score_gemma":0.001145602,"domain_scores_codex":[0.9947426,0.001865236,0.0005085325,0.0009877051,0.001549121,0.0003467375],"domain_scores_gemma":[0.9897228,0.006831637,0.0007008971,0.0008230171,0.001763176,0.000158364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004051968,0.0001316687,0.001020354,0.0001379976,0.0001192325,0.000438843,0.0003303713,0.7791516,0.01496368,0.07504889,0.001184335,0.1270678],"study_design_scores_gemma":[0.00002829006,0.00008002016,0.00009712683,0.00001249821,0.00001814384,0.000114655,0.00001242683,0.9758736,0.004936589,0.01830263,0.0005037631,0.00002017974],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01172079,0.00009406982,0.9870241,0.00009815719,0.00002824626,0.00005207643,0.0000250852,0.00008821338,0.0008692617],"genre_scores_gemma":[0.7111951,0.0002280014,0.2862225,0.0001759281,0.0001055107,0.0002314822,0.0001632627,0.00005436793,0.001623843],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00467012,"threshold_uncertainty_score":0.0246982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675608141423036,"score_gpt":0.2607929800481408,"score_spread":0.2340368986339105,"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."}}