{"id":"W3005028058","doi":"10.3390/app10031027","title":"3D Numerical Modeling of Induced-Polarization Grounded Electrical-Source Airborne Transient Electromagnetic Response Based on the Fictitious Wave Field Methods","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Finite-difference time-domain method; Amplitude; Maxwell's equations; Time domain; Electromagnetic field; Electrical conductor; Polarization (electrochemistry); Transient (computer programming); Transient response; Physics; Frequency domain; Acoustics; Computer science; Mathematical analysis; Engineering; Optics; Classical mechanics; Mathematics; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001480392,0.0001887982,0.0002821048,0.00009537258,0.0003728082,0.0000706444,0.0004207802,0.00009771677,0.0003614202],"category_scores_gemma":[0.0008323126,0.0001187307,0.0000944947,0.002318821,0.0001277965,0.00006770276,0.00001170009,0.0003868968,0.00002659902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006151236,"about_ca_system_score_gemma":0.0001266797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002595942,"about_ca_topic_score_gemma":0.000007970284,"domain_scores_codex":[0.99734,0.0007688394,0.0003328185,0.0004962364,0.0006019353,0.0004601427],"domain_scores_gemma":[0.9958302,0.003671283,0.0001024016,0.0001760496,0.00004168329,0.0001783777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002156245,0.0001768409,0.0001906,0.00002239916,0.00002453069,0.000004537734,0.0008344759,0.1873963,0.07768729,0.003746784,0.000102467,0.7276575],"study_design_scores_gemma":[0.0001807098,0.002720674,0.005095378,0.000004722638,0.00002020369,0.000001259689,0.00005757807,0.9762991,0.01313366,0.002156954,0.0001589094,0.0001708332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5194561,0.00006687542,0.4660273,0.008372776,0.0000659881,0.0004027247,0.000003925888,0.000078915,0.005525339],"genre_scores_gemma":[0.9610918,0.000002641018,0.03425815,0.004561855,0.00006026964,0.000006490126,0.000004058911,0.000004192548,0.00001053473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7889028,"threshold_uncertainty_score":0.4841698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03836056945950065,"score_gpt":0.2626015443603318,"score_spread":0.2242409749008311,"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."}}