{"id":"W1595713750","doi":"10.1109/sam.2006.1706179","title":"Multiple Window Bispectrum Estimator","year":2006,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Bispectrum; Estimator; Higher-order statistics; Algorithm; Mathematics; Nonparametric statistics; Computer science; Applied mathematics; Signal processing; Statistics; Spectral density; Digital signal processing","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":[0.0001240373,0.00007068936,0.00006799192,0.00007426958,0.0000708852,0.0001436046,0.0003899566,0.00003598093,0.00002842872],"category_scores_gemma":[0.00001479066,0.00006130767,0.00003265564,0.0002077134,0.00001734408,0.0003603226,0.0000881892,0.00005807052,0.0001587816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001571019,"about_ca_system_score_gemma":0.00002762698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001852069,"about_ca_topic_score_gemma":0.00008452122,"domain_scores_codex":[0.9993773,0.0000236621,0.000122919,0.0001911151,0.0001411058,0.0001439462],"domain_scores_gemma":[0.9995166,0.00004728725,0.00003241512,0.0003436317,0.00002865242,0.00003139907],"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":[8.071449e-7,0.00004972259,0.003491134,0.000001306399,0.000001681552,0.000003820393,0.00004399724,0.00009650265,0.002824078,0.9767184,0.01485629,0.001912304],"study_design_scores_gemma":[0.0006564187,0.0001092107,0.04325711,0.000009357993,0.000002703457,0.00003687259,0.0000122088,0.3330136,0.4102944,0.1447431,0.06734034,0.0005247631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007799726,0.00001307355,0.9363961,0.002332827,0.00005589527,0.0000928213,3.727494e-7,0.001235987,0.05207318],"genre_scores_gemma":[0.6861807,4.154152e-7,0.3119697,0.0004312764,0.00002405026,0.000008059641,0.00000122539,0.000003936892,0.001380661],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8319753,"threshold_uncertainty_score":0.2500054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006675744527724177,"score_gpt":0.2214054565901289,"score_spread":0.2147297120624047,"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."}}