{"id":"W3129172140","doi":"10.3390/app11031331","title":"Multiple Narrowband Interferences Characterization, Detection and Mitigation Using Simplified Welch Algorithm and Notch Filtering","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec; École de technologie supérieure","keywords":"Computer science; Bandwidth (computing); Electronic engineering; Band-stop filter; Narrowband; Detector; Telecommunications; Engineering; Low-pass filter","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":[0.0001320056,0.0001030038,0.0001067826,0.0000765323,0.0003766659,0.0001978665,0.0001084144,0.00004828806,0.00001137853],"category_scores_gemma":[0.00002389884,0.0001077592,0.00001000185,0.0003401776,0.0001695028,0.0002567026,0.00007697065,0.00008627314,0.000001440214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002112134,"about_ca_system_score_gemma":0.00001809334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001578401,"about_ca_topic_score_gemma":0.00007427025,"domain_scores_codex":[0.9993389,0.00001888327,0.0001671796,0.0002157641,0.0001115355,0.0001478003],"domain_scores_gemma":[0.9996538,0.00009010251,0.00003721318,0.0001336033,0.00003824784,0.00004706385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.887168e-7,0.000004151428,0.0004376952,0.00001874188,0.000006011258,3.176576e-7,0.0005056694,0.00666822,0.9577661,0.00009815681,9.499055e-7,0.03449312],"study_design_scores_gemma":[0.0001134195,0.000007160589,0.007475969,0.00002350408,0.000005846404,0.0000136776,0.0005200367,0.7356988,0.2558607,0.00005031262,0.0001060324,0.0001245912],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9222894,0.000133965,0.077085,0.00004717161,0.0001119862,0.0000893518,0.000009375791,0.00009773211,0.0001360679],"genre_scores_gemma":[0.9858855,0.000097863,0.01390793,0.00002116202,0.00003498937,0.00002150011,0.0000148418,0.000009594015,0.000006602979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7290305,"threshold_uncertainty_score":0.4394295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02065048374621701,"score_gpt":0.2279044648684951,"score_spread":0.2072539811222781,"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."}}