{"id":"W4403219919","doi":"10.1190/geo2023-0726.1","title":"3D airborne electromagnetic forward modeling based on the multiscale hexahedral finite-element method","year":2024,"lang":"en","type":"article","venue":"Geophysics","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Hexahedron; Finite element method; Computer science; Geology; Engineering; Structural engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002240501,0.0003802264,0.000363969,0.0003936818,0.0002511899,0.000468077,0.0006271199,0.0005943196,0.00208956],"category_scores_gemma":[0.0005288848,0.0002424205,0.0006553783,0.0002649202,0.0003244764,0.0003227025,0.0005435049,0.0004374115,0.0003730335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003062177,"about_ca_system_score_gemma":0.0006211779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008074409,"about_ca_topic_score_gemma":0.005953981,"domain_scores_codex":[0.9998828,0.00002530984,0.000007537292,0.00001728402,0.00005669723,0.00001028421],"domain_scores_gemma":[0.9998078,0.00006646848,0.00002532562,0.0000239386,0.00006364667,0.00001289685],"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":[0.00001640096,0.00002266099,0.0009559426,0.0000343921,0.00001857517,0.00008150782,0.0000503835,0.9706925,0.009737396,0.005171763,0.0003484614,0.01286996],"study_design_scores_gemma":[0.000002555987,0.000004636247,0.00009892268,0.00000237259,0.000001496295,0.00001048207,0.000004625007,0.9987147,0.0004310202,0.0002754559,0.0004510895,0.000002600827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04338156,0.00008373678,0.9505034,0.0001339228,0.00004357618,0.00005471758,0.000178978,0.0006386689,0.004981404],"genre_scores_gemma":[0.615999,0.0002389002,0.3790233,0.000106082,0.00003155764,0.0001872949,0.0003353652,0.0001711286,0.00390735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008074409,"threshold_uncertainty_score":0.01605481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02169725022127442,"score_gpt":0.2952334714286557,"score_spread":0.2735362212073812,"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."}}