{"id":"W2597465542","doi":"10.1111/1365-2478.12529","title":"Electric field data in inductive source electromagnetic surveys","year":2017,"lang":"en","type":"article","venue":"Geophysical Prospecting","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Universiti Teknikal Malaysia Melaka","keywords":"Electric field; Inversion (geology); Geology; Geophysics; Electromagnetic field; Electromagnetic induction; Computer science; Physics; Electrical engineering; Seismology; Electromagnetic coil; Engineering","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":[0.0005086979,0.0002801992,0.0001858477,0.0009998926,0.0001187339,0.0003749531,0.0004086152,0.0003813199,0.0005512367],"category_scores_gemma":[0.002300742,0.0001488706,0.0002062891,0.0008614751,0.0003567618,0.000578022,0.000417706,0.0002582629,0.0001430499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002391372,"about_ca_system_score_gemma":0.0001755292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001786479,"about_ca_topic_score_gemma":0.001262522,"domain_scores_codex":[0.9997388,0.00008016893,0.00001465035,0.00006092611,0.00007811966,0.00002744864],"domain_scores_gemma":[0.9992237,0.0003375459,0.000125714,0.0001229904,0.0001621277,0.00002797104],"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":[0.001043289,0.0002353266,0.1079197,0.0002405211,0.0001143133,0.0006725646,0.0004245553,0.4746633,0.2330345,0.006062449,0.001231982,0.1743575],"study_design_scores_gemma":[0.00007479195,0.000307452,0.09337416,0.00003450068,0.00005581448,0.0004458703,0.0003036719,0.7815574,0.1118508,0.007745428,0.004148156,0.0001020321],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8413237,0.00007119434,0.1548227,0.00009905653,0.00001519061,0.00003274872,0.0004393143,0.0004558343,0.002740372],"genre_scores_gemma":[0.9849247,0.00003140619,0.01427342,0.00001528879,0.000005062722,0.000008501157,0.000403133,0.00002092387,0.0003175696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001786479,"threshold_uncertainty_score":0.003552139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03356087468436213,"score_gpt":0.2826283347550201,"score_spread":0.249067460070658,"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."}}