{"id":"W1922005389","doi":"10.1190/geo2014-0467.1","title":"5D seismic data completion and denoising using a novel class of tensor decompositions","year":2015,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Computing and Communication Foundations; University of Alberta; National Science Foundation","keywords":"Missing data; Singular value decomposition; Algorithm; Synthetic data; Interpolation (computer graphics); Tensor (intrinsic definition); Computer science; Low-rank approximation; Regularization (linguistics); Undersampling; Noise reduction; Mathematics; Data mining; Artificial intelligence; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001568354,0.001116386,0.0007684654,0.001038215,0.0003618226,0.0008618449,0.0008576686,0.0007105505,0.0009738809],"category_scores_gemma":[0.003358512,0.000357269,0.00116719,0.0009535449,0.0009679515,0.001281414,0.00118778,0.001386591,0.0003680607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006030124,"about_ca_system_score_gemma":0.001233199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003093379,"about_ca_topic_score_gemma":0.003043115,"domain_scores_codex":[0.9991248,0.0002224872,0.00007387035,0.0001582511,0.0003481736,0.00007248552],"domain_scores_gemma":[0.9984564,0.0004333648,0.0002603808,0.000303445,0.0004356064,0.0001107524],"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":[0.0003062027,0.0001640262,0.001967524,0.0002607916,0.0001565696,0.0002282481,0.0002807241,0.5761201,0.08519509,0.07445387,0.002606323,0.2582605],"study_design_scores_gemma":[0.000004107829,0.00002319785,0.0001325082,0.000003644829,0.000003754903,0.00002572886,0.000006194414,0.9919102,0.003861003,0.003304439,0.000716389,0.000008839103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008125185,0.00004591284,0.9913799,0.00004869753,0.00001456245,0.00001625005,0.00003529198,0.0001167251,0.00021732],"genre_scores_gemma":[0.1345609,0.0001875972,0.863515,0.00005357648,0.00004864276,0.00007926053,0.0003376064,0.00009157699,0.001125858],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003093379,"threshold_uncertainty_score":0.008294284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288339369547438,"score_gpt":0.2777017385584067,"score_spread":0.148867801603663,"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."}}