{"id":"W2161103889","doi":"10.14288/1.0107398","title":"Application of stable signal recovery to seismic interpolation","year":2008,"lang":"en","type":"article","venue":"Open Collections","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Interpolation (computer graphics); Solver; Signal recovery; SIGNAL (programming language); Minification; Algorithm; Curvelet; Computer science; Synthetic data; Scale (ratio); Geology; Seismic exploration; Mathematical optimization; Seismology; Mathematics; Compressed sensing; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001132081,0.00004784968,0.00008309529,0.00008336492,0.0006793621,0.00007854964,0.0001725508,0.0000250082,0.002060673],"category_scores_gemma":[0.00001457346,0.00004670523,0.00002379256,0.0006562561,0.00002634999,0.0003077573,0.00001694745,0.00004964711,0.0000661408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008483425,"about_ca_system_score_gemma":0.00006910203,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1038617,"about_ca_topic_score_gemma":0.0004049089,"domain_scores_codex":[0.9995371,0.00002865929,0.0001306166,0.0001298917,0.00008477241,0.0000889653],"domain_scores_gemma":[0.9996941,0.00004363094,0.00004960192,0.0001144153,0.00005293198,0.00004533015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000447223,0.00002000686,0.002612678,0.000002430534,0.000007050908,3.914392e-7,0.0001077798,0.003548503,0.0001568969,0.000003239116,0.9739768,0.01951952],"study_design_scores_gemma":[0.000200106,0.0003383874,0.004658486,0.00002063317,0.000009847813,0.00003475989,0.0002051188,0.3314134,0.007295437,0.00136543,0.6542902,0.0001681272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007931802,0.00008631108,0.2936936,0.0008949047,0.0002605161,0.0009280902,0.0001475203,0.0001199789,0.6959372],"genre_scores_gemma":[0.8775039,0.0000615156,0.01193645,0.00224807,0.00004244093,0.0000170034,0.00007848511,0.00000391181,0.1081082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8695721,"threshold_uncertainty_score":0.9988516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750656384277293,"score_gpt":0.2280914697536159,"score_spread":0.2105849059108429,"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."}}