{"id":"W2791933444","doi":"10.1071/aseg2018abp071","title":"3D Inversion of Large Scale Marine Controlled-Source Electromagnetics","year":2018,"lang":"en","type":"article","venue":"ASEG Extended Abstracts","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geoscience BC; University of British Columbia","funders":"","keywords":"Isotropy; Computer science; Bathymetry; Polygon mesh; Inversion (geology); Inverse problem; Electromagnetics; Geophysics; Computational science; Mathematical optimization; Geology; Electronic engineering; Physics; Mathematics; Mathematical analysis; Engineering; Optics","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":[0.0003513992,0.0004249875,0.0003328387,0.0005077757,0.0002690694,0.0009925166,0.000812616,0.0009550123,0.002529573],"category_scores_gemma":[0.001978659,0.0003713626,0.0005537233,0.000570705,0.0004963469,0.0006408973,0.0009594018,0.0008139768,0.0004279642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003504807,"about_ca_system_score_gemma":0.0009777434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005185692,"about_ca_topic_score_gemma":0.005112301,"domain_scores_codex":[0.9998624,0.0000257177,0.000008369868,0.00002049192,0.00006805819,0.00001489579],"domain_scores_gemma":[0.9995263,0.0002459074,0.00003809126,0.00006333507,0.0000987981,0.00002756165],"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":[0.00002805483,0.0000399758,0.001479977,0.00008213665,0.00002128163,0.0001684171,0.00009440257,0.957389,0.01083628,0.01026916,0.00136675,0.01822457],"study_design_scores_gemma":[0.000009609921,0.000006577766,0.0002827778,0.000005615257,0.000002221872,0.00002192965,0.00001898626,0.994739,0.001592022,0.001987395,0.001327103,0.000006833327],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06307237,0.0001103661,0.9276951,0.0003064798,0.00009850317,0.00006578028,0.0007357981,0.0009867547,0.006928849],"genre_scores_gemma":[0.6761503,0.0002989795,0.3176436,0.0001791535,0.00007999917,0.0001765921,0.001442317,0.0002440926,0.003785002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005185692,"threshold_uncertainty_score":0.01031101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007271381171049423,"score_gpt":0.2305907852586506,"score_spread":0.2233194040876011,"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."}}