{"id":"W4285208947","doi":"10.3997/2214-4609.202210382","title":"Coherent Noise Suppression Via a Self-Supervised Deep Learning Scheme","year":2022,"lang":"en","type":"article","venue":"83rd EAGE Annual Conference &amp; Exhibition","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Noise (video); Computer science; Noise reduction; Artificial intelligence; Noise measurement; Artificial neural network; Synthetic data; TRACE (psycholinguistics); Deep learning; Pattern recognition (psychology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001030489,0.0005881623,0.0006572952,0.0004015463,0.0002937322,0.0004465941,0.001325641,0.0008415916,0.001182916],"category_scores_gemma":[0.001743546,0.0003340231,0.0005521876,0.0003395692,0.0007072341,0.0007260276,0.001325035,0.001084681,0.0004118819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004623362,"about_ca_system_score_gemma":0.0009680128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002128382,"about_ca_topic_score_gemma":0.003797002,"domain_scores_codex":[0.9995083,0.0001169645,0.00002528029,0.00009785059,0.0001920215,0.00005963533],"domain_scores_gemma":[0.9992045,0.0002051091,0.00009998334,0.0001398011,0.0003026535,0.00004807306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000158514,0.0001675748,0.000919836,0.00007213451,0.0000845838,0.00009030222,0.0001060318,0.7861869,0.02643958,0.01144174,0.0027488,0.171584],"study_design_scores_gemma":[0.000002525372,0.00001165041,0.00002539458,0.00000118621,0.000001851717,0.000003586588,0.000001173689,0.9983553,0.0009423839,0.0005584982,0.00009446838,0.000001933226],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02831311,0.00006882708,0.9695684,0.0001195101,0.00002429252,0.00002817963,0.00002381551,0.0005708616,0.001283078],"genre_scores_gemma":[0.703805,0.00007978075,0.2902455,0.0002796659,0.00006232833,0.000128644,0.0002393348,0.0001303676,0.005029277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002128382,"threshold_uncertainty_score":0.005449831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000847941425792,"score_gpt":0.2310783120717034,"score_spread":0.2110698326574454,"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."}}