{"id":"W4312219782","doi":"10.1093/gji/ggac519","title":"A fully finite-element based model-space algorithm for three-dimensional inversion of magnetotelluric data","year":2022,"lang":"en","type":"article","venue":"Geophysical Journal International","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Solver; Finite element method; Magnetotellurics; Algorithm; Basis function; Discretization; Computer science; Mathematical optimization; Applied mathematics; Mathematics; Mathematical analysis; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004312104,0.0004598535,0.0004932478,0.000324426,0.0003925379,0.0007707099,0.001425954,0.0009298176,0.005188189],"category_scores_gemma":[0.0009463618,0.0004432045,0.0005961324,0.0003082402,0.000435734,0.0005368676,0.001040793,0.001012913,0.001739995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005155251,"about_ca_system_score_gemma":0.001056783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003719856,"about_ca_topic_score_gemma":0.004796164,"domain_scores_codex":[0.9997633,0.00003762371,0.00001328359,0.00002889903,0.0001381879,0.00001884119],"domain_scores_gemma":[0.9997287,0.00008890311,0.00002208436,0.00004495939,0.0001008596,0.00001451123],"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":[0.00005363903,0.00005293945,0.000411394,0.00007428671,0.00003061861,0.00006587459,0.0001345194,0.8519825,0.01984404,0.01725469,0.002403407,0.1076921],"study_design_scores_gemma":[0.000005033379,0.000006992408,0.00003436395,0.000003482153,0.000001386223,0.00001082366,0.000006262027,0.9948958,0.00171439,0.001419383,0.001897616,0.000004481769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001642757,0.00001107285,0.9971842,0.00002737738,0.000004944331,0.00001550587,0.00002211758,0.0005033925,0.000588542],"genre_scores_gemma":[0.07925693,0.00003114004,0.9173438,0.00005851368,0.000005700184,0.0002065197,0.0002314309,0.0002474561,0.00261859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005188189,"threshold_uncertainty_score":0.01735628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03693721629890425,"score_gpt":0.2677392111022146,"score_spread":0.2308019948033103,"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."}}