{"id":"W1987097187","doi":"10.1007/s00024-006-0088-0","title":"A Study of the Adaptive Method for Decoupling Overlapping Seismic Records","year":2006,"lang":"en","type":"article","venue":"Pure and Applied Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Deconvolution; Decoupling (probability); Computer science; A priori and a posteriori; Algorithm; Noise reduction; Seismology; SIGNAL (programming language); Reduction (mathematics); Geology; Mathematics; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001709817,0.00009397007,0.0001474889,0.00002440583,0.0001737542,0.00001983406,0.0001156606,0.00003063519,0.000007066043],"category_scores_gemma":[0.000002766583,0.00006514483,0.00004150895,0.0001399061,0.00003287915,0.00004682876,0.00001590184,0.00008415061,0.000001913574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002006913,"about_ca_system_score_gemma":0.00001571377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00277917,"about_ca_topic_score_gemma":0.00008251461,"domain_scores_codex":[0.9994175,0.00001647983,0.0001364441,0.0001778738,0.0001114562,0.0001402049],"domain_scores_gemma":[0.9996024,0.0001307144,0.00009529663,0.0001284367,0.00002483708,0.00001825885],"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":[0.0003204824,0.0004084106,0.05928468,0.0001313686,0.0001793488,0.000001769002,0.003942016,0.02256849,0.001480738,0.005795967,0.0138357,0.892051],"study_design_scores_gemma":[0.002729657,0.001016992,0.1581314,0.00009959268,0.0003883631,0.00001027474,0.01015373,0.526139,0.01758452,0.2645639,0.01823609,0.0009465203],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737319,0.00007127452,0.02107215,0.00009662982,0.0001061153,0.0005339127,0.00002791992,0.00004306559,0.00431705],"genre_scores_gemma":[0.9930671,0.00000393644,0.006323239,0.0003602251,0.0001046225,0.000007467333,0.000009026987,0.000003494193,0.000120841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8911045,"threshold_uncertainty_score":0.4201292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0144233982440944,"score_gpt":0.2296322807808545,"score_spread":0.2152088825367601,"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."}}