{"id":"W4360602043","doi":"10.1093/gji/ggad122","title":"Impacts of magnetic permeability on electromagnetic data collected in settings with steel-cased wells","year":2023,"lang":"en","type":"article","venue":"Geophysical Journal International","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Casing; Permeability (electromagnetism); Electromagnetic induction; Mechanics; Geology; Magnetization; Frequency domain; Magnetic field; Geophysics; Physics; Computer science; Electrical engineering; Engineering; Electromagnetic coil; Chemistry","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":[0.0007572403,0.0003499288,0.0003356982,0.0004777024,0.0004323623,0.0006962137,0.0004841692,0.0008479313,0.001064718],"category_scores_gemma":[0.003893513,0.0001818937,0.0003333461,0.0005200392,0.0008098821,0.0009256838,0.0005883897,0.0005786888,0.0001829366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005040029,"about_ca_system_score_gemma":0.0002976827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00312058,"about_ca_topic_score_gemma":0.003687672,"domain_scores_codex":[0.9994829,0.0001811522,0.00003695297,0.0000926098,0.0001467855,0.00005955777],"domain_scores_gemma":[0.9983724,0.0009547581,0.0001278197,0.0001582997,0.0003073528,0.00007948218],"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":[0.001744758,0.000945733,0.1128814,0.0004454392,0.0001448313,0.002214051,0.001194374,0.6014115,0.238512,0.003269989,0.002044205,0.03519163],"study_design_scores_gemma":[0.0002111447,0.001802257,0.1497867,0.00008533711,0.00008904988,0.0006086883,0.002331703,0.7209755,0.1163483,0.003810734,0.003708235,0.0002422987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912144,0.00002533372,0.006514002,0.0001226322,0.00002417215,0.00004185901,0.0003787495,0.0001396625,0.00153916],"genre_scores_gemma":[0.997062,0.00001951228,0.002423297,0.0000292092,0.000004510157,0.00001851965,0.0002519543,0.00001382378,0.0001771312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00312058,"threshold_uncertainty_score":0.006204844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01969412362340537,"score_gpt":0.2663889915285344,"score_spread":0.246694867905129,"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."}}