{"id":"W2313027102","doi":"10.1190/segam2013-1355.1","title":"Noise estimation in gravity gradient data after equivalent source processing","year":2013,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada","keywords":"Noise (video); Computer science; Estimation; Acoustics; Physics; Artificial intelligence; Engineering","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":[0.001009252,0.0007961505,0.0006079142,0.001677739,0.0004111189,0.001334909,0.0007158673,0.001110565,0.002195738],"category_scores_gemma":[0.006034589,0.0003421984,0.0005696166,0.00151827,0.0008272995,0.002031975,0.00112577,0.001070861,0.0008843926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003290407,"about_ca_system_score_gemma":0.0005869215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002016965,"about_ca_topic_score_gemma":0.002552558,"domain_scores_codex":[0.9992304,0.0001158953,0.00004484639,0.0001324055,0.0004100667,0.00006640558],"domain_scores_gemma":[0.9986436,0.0004112019,0.00008736936,0.0002652996,0.0005616113,0.000030886],"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":[0.0006767007,0.0001708318,0.00793194,0.0004577878,0.0001124172,0.000829531,0.000787714,0.06173682,0.3402972,0.02682729,0.003939714,0.5562322],"study_design_scores_gemma":[0.00007273308,0.0002374538,0.01803397,0.00008386805,0.0001314638,0.001185374,0.0003996145,0.638998,0.2923664,0.02904205,0.0192555,0.0001936191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05591745,0.0001402129,0.9406425,0.0001664917,0.0001164195,0.00004670251,0.0002115804,0.0007968398,0.001961743],"genre_scores_gemma":[0.3373618,0.0003652913,0.6567549,0.0001439676,0.00007286215,0.00008478783,0.001179087,0.0006174944,0.003419745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002195738,"threshold_uncertainty_score":0.007345498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471500330572888,"score_gpt":0.2433163331662882,"score_spread":0.2186013298605593,"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."}}