{"id":"W2049411559","doi":"10.1190/1.2187772","title":"Model-based separation filtering of magnetic data","year":2006,"lang":"en","type":"article","venue":"Geophysics","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Logarithm; Filter (signal processing); Fractal; Interpretation (philosophy); Spectral density; Source separation; Geology; Field (mathematics); Separation (statistics); Layering; Algorithm; Computer science; Mathematics; Mathematical analysis; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009217312,0.00008609315,0.0001336225,0.00002444712,0.00004662529,0.00001719241,0.0002638103,0.00003157279,0.0001515918],"category_scores_gemma":[0.00001379082,0.00007285641,0.00003517139,0.000256174,0.00003955797,0.0001326467,0.00001696458,0.00006815077,0.00009933077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001008201,"about_ca_system_score_gemma":0.00003240157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001424045,"about_ca_topic_score_gemma":0.0001444096,"domain_scores_codex":[0.999242,0.00003750985,0.0001549443,0.0002048144,0.0001761766,0.0001845684],"domain_scores_gemma":[0.999428,0.0001010944,0.00005403392,0.0003498098,0.00002942682,0.0000376886],"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":[0.00005153895,0.0001237808,0.005970843,0.00006566248,0.000006511392,0.000003184175,0.00002064573,0.4026743,0.005737582,0.0009541446,0.0009951468,0.5833966],"study_design_scores_gemma":[0.0001090528,0.00009886319,0.1247366,0.00000427563,0.00001228924,2.196333e-7,0.000001173398,0.8452411,0.001340219,0.02799068,0.000372902,0.00009259813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9223574,0.0001952216,0.06775824,0.0001138763,0.0001245714,0.0001327377,0.0002625354,0.00004943193,0.009005945],"genre_scores_gemma":[0.9814032,0.000001483524,0.01770782,0.00005496816,0.0001264619,4.645653e-7,0.0004147866,0.000002161505,0.0002887114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.583304,"threshold_uncertainty_score":0.2970998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03581405903655584,"score_gpt":0.2663239937865987,"score_spread":0.2305099347500429,"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."}}