{"id":"W1580433198","doi":"10.1109/isspit.2003.1341071","title":"Adaptive maximum windowed likelihood AM-FM signal decomposition","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Algorithm; Computer science; SIGNAL (programming language); Range (aeronautics); Amplitude; Window (computing); Maximum likelihood; Computational complexity theory; Window function; Mathematics; Statistics; Spectral density; Physics; Telecommunications; Engineering","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":[0.0008071078,0.0005896386,0.0005237078,0.0005395478,0.0002726837,0.0006046416,0.0006754308,0.0007096661,0.003041274],"category_scores_gemma":[0.00216816,0.0002302429,0.0005786469,0.0004802167,0.0003008503,0.0009260119,0.0006422132,0.0005806335,0.00109919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002849061,"about_ca_system_score_gemma":0.0004729209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000530657,"about_ca_topic_score_gemma":0.0006441228,"domain_scores_codex":[0.9995981,0.0001198722,0.00002157259,0.00007846083,0.0001528891,0.00002913946],"domain_scores_gemma":[0.999598,0.0001749871,0.00004535969,0.00004690631,0.0001142562,0.00002051128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003789702,0.0000987652,0.001291645,0.0002659603,0.0000869721,0.0001995991,0.000141973,0.1283587,0.1138844,0.02697179,0.003353174,0.7249681],"study_design_scores_gemma":[0.00002071427,0.00005888574,0.0006074826,0.00001511061,0.00001294438,0.0001321338,0.000009389159,0.976248,0.01368173,0.005103115,0.004094158,0.00001634532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00298794,0.00008473381,0.9962513,0.00003974717,0.00001324786,0.00001561372,0.0000203301,0.0001747845,0.0004123964],"genre_scores_gemma":[0.1392003,0.0001990702,0.8576826,0.00006909691,0.00006005648,0.0001250332,0.0001757955,0.000114785,0.002373314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003041274,"threshold_uncertainty_score":0.01017404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007459538988439,"score_gpt":0.2348353070454453,"score_spread":0.2247607116555609,"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."}}