{"id":"W2891678200","doi":"10.1190/segam2018-2998528.1","title":"3D finite-volume time-domain electromagnetic modeling of graphitic faults using unstructured grids","year":2018,"lang":"en","type":"article","venue":"","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"iNano Medical (Canada); Memorial University of Newfoundland","funders":"","keywords":"Finite volume method; Computer science; Volume (thermodynamics); Computational electromagnetics; Electromagnetic field; Mechanics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006641785,0.0001277376,0.0001805733,0.00007371014,0.00005813516,0.000009675809,0.0001220779,0.00006002319,0.0001976193],"category_scores_gemma":[0.0000180704,0.0001206249,0.00006100807,0.0003685434,0.00006561541,0.00004688646,0.00001924481,0.00009089836,0.00004751063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001429613,"about_ca_system_score_gemma":0.00000983846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003485315,"about_ca_topic_score_gemma":0.000002931684,"domain_scores_codex":[0.9992622,0.00002115038,0.0002197353,0.0001509019,0.0001040743,0.0002419559],"domain_scores_gemma":[0.9995753,0.00004406155,0.00002147225,0.0002338823,0.00006296861,0.00006232567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004680545,0.00002203028,0.00002132386,0.00004044728,0.00003121161,4.019915e-7,0.0001022899,0.08254174,0.9114954,0.002505828,0.00004690467,0.003187731],"study_design_scores_gemma":[0.0001324932,0.00006664242,0.0001777452,0.0000129791,0.00002182125,0.000002235251,0.00001289266,0.9748158,0.006480916,0.01806272,0.00007267464,0.0001410476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6788467,0.00002234539,0.3178857,0.00001345176,0.00004507646,0.00009557835,0.00000551693,0.0001195176,0.002966143],"genre_scores_gemma":[0.7603,0.000002227877,0.2394934,0.00001340112,0.0000994151,0.000006026271,0.000003428916,0.00002053445,0.00006157154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9050145,"threshold_uncertainty_score":0.4918941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005564537206409,"score_gpt":0.2326994191882319,"score_spread":0.2226437738161678,"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."}}