{"id":"W2068140550","doi":"10.1109/ultsym.2014.0137","title":"Echo identification by Singular Value Decomposition of Cross Wigner-Ville Distribution","year":2014,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Echo (communications protocol); Singular value decomposition; Identification (biology); SIGNAL (programming language); Wigner distribution function; Computer science; Distribution (mathematics); Value (mathematics); Decomposition; Mathematics; Algorithm; Physics; Statistics; Mathematical analysis; Chemistry","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":[0.0007222036,0.00007950538,0.0001026995,0.00004569416,0.00009840546,0.0002001021,0.0003799234,0.00007291558,0.000008809187],"category_scores_gemma":[0.00005896912,0.00007860395,0.00004687789,0.000227667,0.00004931758,0.0006791723,0.00006962669,0.00005727454,0.00002225072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004073385,"about_ca_system_score_gemma":0.00001627853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005671299,"about_ca_topic_score_gemma":0.00000183221,"domain_scores_codex":[0.9989618,0.0001335119,0.0003099787,0.0002467193,0.0002351595,0.0001128129],"domain_scores_gemma":[0.9991058,0.00005114575,0.0001732773,0.0004352158,0.0001947336,0.00003980966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005017348,0.000152396,0.0004458825,0.00001318063,0.000007791399,1.357323e-7,0.000318125,0.0003475824,0.2011073,0.7776878,0.006082816,0.01383196],"study_design_scores_gemma":[0.0001540525,0.00006803555,0.002724088,0.000009719565,0.000003367137,0.000002195053,0.000004594206,0.1211594,0.851783,0.02029298,0.003676489,0.0001220134],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0742232,0.00001384886,0.9227573,0.0003454823,0.00007432162,0.000117789,0.000005865944,0.0002941288,0.002168049],"genre_scores_gemma":[0.9694322,0.000003221458,0.0300461,0.000157544,0.00001491046,0.000009068246,0.0001468233,0.00000481347,0.0001853421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.895209,"threshold_uncertainty_score":0.3205376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007050719474893523,"score_gpt":0.2957846403218001,"score_spread":0.2887339208469066,"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."}}