{"id":"W2002714877","doi":"10.1111/j.1365-2478.2007.00597.x","title":"Non‐minimum phase wavelet estimation by non‐linear optimization of all‐pass operators","year":2007,"lang":"en","type":"article","venue":"Geophysical Prospecting","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Wavelet; Mathematics; Algorithm; Wavelet packet decomposition; Stationary wavelet transform; Bandwidth (computing); Second-generation wavelet transform; Cascade algorithm; Discrete wavelet transform; Wavelet transform; Computer science; Artificial intelligence; 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":[0.0009062496,0.0001729547,0.0002658027,0.00008524675,0.0001669078,0.0001056716,0.0003935561,0.00007483937,0.000006678019],"category_scores_gemma":[0.0001626964,0.000164603,0.00008208696,0.0005936736,0.00005040431,0.0006472784,0.0001370774,0.0002133186,0.00002117039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000538849,"about_ca_system_score_gemma":0.00004029051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005248375,"about_ca_topic_score_gemma":4.739457e-7,"domain_scores_codex":[0.99839,0.00004324341,0.0004289436,0.0004058618,0.0003612838,0.0003707368],"domain_scores_gemma":[0.9990054,0.0001591844,0.0002023194,0.0003422841,0.0001883507,0.0001024822],"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":[0.0001336918,0.001285963,0.0001471012,0.0001158377,0.00007241291,0.00005993678,0.00348181,0.04254121,0.7582795,0.00299139,0.0007786375,0.1901125],"study_design_scores_gemma":[0.0008999844,0.0002035215,0.0001368063,0.00002381498,0.000009819423,0.000004030815,0.00001914935,0.7755702,0.2224115,0.0005381921,0.00002463392,0.00015835],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1744088,0.000009849435,0.8243667,0.00009325679,0.0001911687,0.0001993438,0.000001746217,0.00008320354,0.0006459814],"genre_scores_gemma":[0.6179298,7.471326e-7,0.3817206,0.00009986711,0.0001278094,0.000003693846,0.000009176551,0.00001253264,0.00009576452],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.733029,"threshold_uncertainty_score":0.6712316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349052563826257,"score_gpt":0.3073488018673179,"score_spread":0.2938582762290554,"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."}}