{"id":"W2325216019","doi":"10.1190/segam2012-1424.1","title":"Seismic event parameterization in the Fractional Fourier transform domain","year":2012,"lang":"en","type":"article","venue":"","topic":"Mathematical Analysis and Transform Methods","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional Fourier transform; Chirp; Fourier transform; Kernel (algebra); Frequency domain; Algorithm; Time–frequency analysis; Mathematics; Time domain; Short-time Fourier transform; Signal processing; Computer science; Mathematical analysis; Fourier analysis; Physics; Filter (signal processing); Optics; Digital signal processing; Discrete mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006098252,0.0005418946,0.0003821979,0.001031787,0.00033991,0.001080742,0.000609713,0.0007432898,0.002298231],"category_scores_gemma":[0.002434299,0.0002180208,0.0004496432,0.001152973,0.0006569796,0.001999191,0.0004885494,0.0009152553,0.000751735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004174383,"about_ca_system_score_gemma":0.0003770514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001082395,"about_ca_topic_score_gemma":0.000597709,"domain_scores_codex":[0.9997484,0.00005903709,0.00001753479,0.00006309568,0.00008387646,0.00002799421],"domain_scores_gemma":[0.9996135,0.0001559669,0.00005792959,0.00008492326,0.00007399661,0.00001379317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002234915,0.00007760132,0.001812517,0.0001802377,0.00004166708,0.0004190154,0.0003021951,0.381715,0.09570411,0.2695813,0.002566457,0.2473764],"study_design_scores_gemma":[0.000009188841,0.0000336379,0.00140717,0.0000200503,0.00001639799,0.0003364376,0.00007941121,0.8999946,0.0131111,0.07275779,0.01219111,0.00004309614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01015178,0.0001181238,0.9874671,0.00006560543,0.0000235144,0.00001549817,0.00005329611,0.0001831789,0.001921847],"genre_scores_gemma":[0.4448484,0.000965458,0.5489818,0.0001005469,0.0001537613,0.0001192312,0.0004330043,0.000288827,0.00410896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002298231,"threshold_uncertainty_score":0.007688344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06126007957815695,"score_gpt":0.3643290827252186,"score_spread":0.3030690031470616,"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."}}