{"id":"W1508881944","doi":"10.1109/iscas.1988.15038","title":"Multistage implementation of parameter-invariant null filter and its application to discrimination of closely spaced sinusoids","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Discriminator; Null (SQL); Invariant (physics); Cascade; Filter (signal processing); Filtering theory; Mathematics; Algorithm; Control theory (sociology); Computer science; Artificial intelligence; Engineering; Detector; Data mining; Computer vision; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0001872262,0.00007082101,0.00010258,0.00008470342,0.00003290096,0.00003318117,0.0001246251,0.00002433481,0.00001444957],"category_scores_gemma":[0.00004588564,0.00006295529,0.00001795807,0.0002211383,0.00001067938,0.0003178855,0.00003933438,0.00002367531,0.000003140439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001490433,"about_ca_system_score_gemma":0.00002819669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005484651,"about_ca_topic_score_gemma":0.00006713867,"domain_scores_codex":[0.9992844,0.0000325535,0.0002168447,0.000206299,0.0001487126,0.0001111653],"domain_scores_gemma":[0.9995213,0.00004484789,0.0001276216,0.0001598178,0.00009958912,0.00004688607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007458875,0.00007600745,0.001995672,0.000118131,0.00001077423,0.000001053481,0.002104747,0.00003614032,0.8035774,0.04345169,0.00009354815,0.1485274],"study_design_scores_gemma":[0.000294909,0.00008800719,0.01029526,0.00001319441,0.000005424051,0.000003229811,0.0002090631,0.003238423,0.9846215,0.001048068,0.000103769,0.00007917811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4247757,0.00002004748,0.5744717,0.0002080757,0.00001907005,0.0001807755,0.000002942595,0.00001512794,0.000306592],"genre_scores_gemma":[0.8523828,0.000002800929,0.1474445,0.00008334115,0.000004322748,0.00001445107,0.000003012433,0.000003330774,0.00006140061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4276071,"threshold_uncertainty_score":0.2567242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02145393784486048,"score_gpt":0.2928782065572464,"score_spread":0.271424268712386,"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."}}