{"id":"W2014587165","doi":"10.1139/e01-003","title":"Time-frequency analysis of deep crustal reflection seismic data using Wigner-Ville distributions","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Earth Sciences","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique","keywords":"Skeletonization; Instantaneous phase; Geology; Reflection (computer programming); Hilbert–Huang transform; Seismology; Energy (signal processing); Geophysics; Computer science; Radar; Artificial intelligence; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.001212449,0.0004524875,0.0003597641,0.00296665,0.0002186766,0.000870671,0.0004572141,0.0002877155,0.001813821],"category_scores_gemma":[0.004843911,0.0002126232,0.000306949,0.002219099,0.0003049597,0.001170238,0.0005362125,0.0004267376,0.0004748787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003792578,"about_ca_system_score_gemma":0.0003888895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003282927,"about_ca_topic_score_gemma":0.003401193,"domain_scores_codex":[0.9996954,0.00007184628,0.00002385326,0.00004576921,0.000124448,0.00003876256],"domain_scores_gemma":[0.9982483,0.001203358,0.0001661258,0.0001209503,0.0002191937,0.00004200359],"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":[0.0002639135,0.0001353981,0.01170382,0.0001771911,0.0001049296,0.0006730484,0.0006161,0.3125296,0.08074789,0.1165771,0.001787716,0.4746833],"study_design_scores_gemma":[0.00001048158,0.00003551064,0.003780391,0.00001001448,0.00001095929,0.0002136466,0.00009799287,0.961808,0.008422056,0.02279114,0.002795954,0.00002397839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05286411,0.00008460486,0.9452472,0.00004368088,0.000004822849,0.00002142688,0.0001533717,0.0004739519,0.001106728],"genre_scores_gemma":[0.6491922,0.0003755428,0.3471028,0.00002198643,0.00002349003,0.0000874688,0.001141299,0.0002288536,0.001826433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003282927,"threshold_uncertainty_score":0.006527662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0455515330707062,"score_gpt":0.2691835553203984,"score_spread":0.2236320222496923,"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."}}