{"id":"W3091233465","doi":"10.1190/tle39100711.1","title":"Edge-aware filtering with Siamese neural networks","year":2020,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"ExxonMobil (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Interpretability; Convolutional neural network; Leverage (statistics); Artificial neural network; Discriminative model; Machine learning; Data mining","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":[0.0006788792,0.000569015,0.0005028467,0.0005792883,0.0002690032,0.0006605916,0.0008643735,0.0008510914,0.001527884],"category_scores_gemma":[0.001990546,0.0003073121,0.0004750648,0.0007306315,0.0006535458,0.001188096,0.0006155954,0.001142176,0.0004130654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006154443,"about_ca_system_score_gemma":0.0006680536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009823916,"about_ca_topic_score_gemma":0.0107386,"domain_scores_codex":[0.9997886,0.00004222597,0.00001208189,0.0000621295,0.00006862958,0.00002637059],"domain_scores_gemma":[0.9992793,0.000329508,0.00006761332,0.0001174356,0.0001743545,0.00003172752],"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":[0.0001326875,0.00007896565,0.00130741,0.00003829704,0.0000616141,0.0000708798,0.00005657053,0.777733,0.02027485,0.01147238,0.001826916,0.1869464],"study_design_scores_gemma":[0.000001498599,0.000007954239,0.00009629014,0.000001210176,0.000001882253,0.000005454131,0.000001779996,0.996655,0.001570354,0.001421566,0.0002338689,0.000003072206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03122217,0.0001217929,0.9668475,0.0001567724,0.00003065234,0.00001463055,0.00005275219,0.0005797008,0.0009739682],"genre_scores_gemma":[0.6058851,0.0002394562,0.3874758,0.0002385038,0.0000888713,0.0000548823,0.000387503,0.000157998,0.005472021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009823916,"threshold_uncertainty_score":0.01953346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02591735021585087,"score_gpt":0.2149595141438335,"score_spread":0.1890421639279827,"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."}}