{"id":"W2148106017","doi":"10.5194/npg-12-373-2005","title":"Deeper understanding of non-linear geodetic data inversion using a quantitative sensitivity analysis","year":2005,"lang":"en","type":"article","venue":"Nonlinear processes in geophysics","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst","keywords":"Sensitivity (control systems); Inversion (geology); Mathematics; Sobol sequence; Geodesy; Applied mathematics; Geology; Statistics","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":[0.002759452,0.0006927982,0.000536003,0.0007254817,0.0002298976,0.0008436703,0.0003179574,0.0003671329,0.001159611],"category_scores_gemma":[0.006619236,0.0002689545,0.0006192676,0.0004755682,0.0007136994,0.0009828049,0.0006435381,0.0006125558,0.0001136781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005809499,"about_ca_system_score_gemma":0.0006815597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002842343,"about_ca_topic_score_gemma":0.001231978,"domain_scores_codex":[0.9990742,0.0005569914,0.00003038994,0.00007581992,0.0002141858,0.00004844651],"domain_scores_gemma":[0.9972221,0.002255781,0.0001182684,0.0001492328,0.000229801,0.00002488121],"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":[0.00006269401,0.00004240601,0.002101637,0.0001156089,0.0000927064,0.0001018542,0.000142312,0.9345134,0.01404032,0.01904315,0.0002215703,0.02952232],"study_design_scores_gemma":[0.000003748848,0.00002123132,0.0009540888,0.000007275515,0.000007083991,0.00001916625,0.00002059481,0.9899048,0.0025429,0.006249785,0.0002605366,0.000008743074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0592547,0.0001011017,0.9378061,0.0001949217,0.00001283612,0.00004688661,0.00005784303,0.0001920069,0.002333602],"genre_scores_gemma":[0.9098595,0.0001093529,0.08895596,0.00007234576,0.00001589028,0.00007899432,0.00006860542,0.00006542244,0.0007737972],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002842343,"threshold_uncertainty_score":0.0145936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1209050328136914,"score_gpt":0.3146077946975581,"score_spread":0.1937027618838666,"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."}}