{"id":"W1531452349","doi":"10.1109/iccw.2015.7247309","title":"Sequential hard-decision fusion for agile cooperative spectrum sensing","year":2015,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"False alarm; Computer science; Fusion center; Reliability (semiconductor); Influence diagram; Fusion; Decision rule; Optimal decision; Agile software development; ALARM; Data mining; Decision analysis; Decision support system; Spectrum (functional analysis); Sensor fusion; Decision tree; Reliability engineering; Artificial intelligence; Engineering; Statistics; Cognitive radio; Mathematics","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":[0.003615264,0.0006164411,0.0005082081,0.0004493221,0.0004429369,0.001074991,0.0006944169,0.0004539932,0.0008917659],"category_scores_gemma":[0.01231206,0.0002807487,0.0003233998,0.0004212296,0.0008282002,0.001005872,0.0008263107,0.0008673531,0.0001658987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006579248,"about_ca_system_score_gemma":0.0007649099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001144956,"about_ca_topic_score_gemma":0.0009415083,"domain_scores_codex":[0.9973706,0.0009023566,0.0001465521,0.0003346726,0.000985346,0.0002604762],"domain_scores_gemma":[0.989578,0.008049451,0.0008349033,0.0006403332,0.000744104,0.000153253],"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":[0.001538816,0.0002077227,0.002798437,0.0001808774,0.0001210756,0.0003310681,0.0003828411,0.730714,0.03017555,0.05277555,0.001000553,0.1797736],"study_design_scores_gemma":[0.00003530821,0.0001812815,0.0003477019,0.000009542281,0.00001680226,0.0001092126,0.00002746787,0.9796621,0.007251369,0.01188057,0.0004625819,0.00001610746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1425084,0.0004556554,0.8535954,0.0001695079,0.00007157033,0.00007649994,0.00003452805,0.0002876209,0.002800886],"genre_scores_gemma":[0.9571031,0.0001107871,0.04210028,0.00006281787,0.00002257814,0.00003473127,0.00001689922,0.00001571534,0.0005330841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003615264,"threshold_uncertainty_score":0.01911956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04298598461376325,"score_gpt":0.2752520314643964,"score_spread":0.2322660468506332,"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."}}