{"id":"W1552858409","doi":"10.1111/1365-2478.12088","title":"Spectral decomposition and de‐noising via time‐frequency and space‐wavenumber reassignment","year":2013,"lang":"en","type":"article","venue":"Geophysical Prospecting","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Deconvolution; Thresholding; Energy (signal processing); Computer science; Seismic trace; Frequency domain; Noise (video); Algorithm; Seismic migration; Time domain; Time–frequency analysis; Passive seismic; Geology; Mathematics; Seismology; Artificial intelligence; Telecommunications; Statistics; Computer vision; Image (mathematics)","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":[0.000134364,0.0001079622,0.0001193938,0.00003168881,0.0002255694,0.0001247033,0.000047323,0.0000377249,0.0003192406],"category_scores_gemma":[0.0000174023,0.0000948508,0.0000245383,0.00007418303,0.000086081,0.0003008257,0.00001515295,0.000152674,0.000182277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001345998,"about_ca_system_score_gemma":0.000009363474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007245181,"about_ca_topic_score_gemma":0.000005880297,"domain_scores_codex":[0.9992313,0.00003657941,0.000110389,0.000236361,0.0001165912,0.0002687825],"domain_scores_gemma":[0.9996732,0.00006384663,0.00004978198,0.00008226124,0.00001842276,0.0001124331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000206334,0.00006156835,0.583624,0.00006215269,0.00003283728,0.00002530737,0.001001706,0.00002420497,0.06893495,0.0007101689,0.002301778,0.3432007],"study_design_scores_gemma":[0.0002770689,0.0002283285,0.7418106,0.00008161455,0.00002259748,0.0001402901,0.0001141657,0.1226059,0.01403454,0.1201965,0.0001272808,0.0003611165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915162,0.00009300979,0.0007956224,0.0008010326,0.0000442267,0.0001658648,0.000002158758,0.0001234654,0.006458436],"genre_scores_gemma":[0.9902437,0.000009105963,0.009096856,0.0003269844,0.0001505966,0.00000173429,0.000007831471,0.000004291059,0.0001589196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3428396,"threshold_uncertainty_score":0.9993657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004699372135718793,"score_gpt":0.2019096832211741,"score_spread":0.1972103110854553,"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."}}