{"id":"W2114108356","doi":"10.1190/segam2014-1433.1","title":"ArjunAir: Updating and parallelizing an existing time domain electromagnetic inversion program","year":2014,"lang":"en","type":"article","venue":"","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Inversion (geology); Time domain; Parallel computing; Computational science; Geology","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":[0.001946112,0.0008274919,0.0008127069,0.0007712987,0.0007132334,0.001330433,0.003560847,0.0006009329,0.007224537],"category_scores_gemma":[0.003949074,0.0006561886,0.001007487,0.0009194192,0.0006389697,0.001628881,0.001755728,0.001666336,0.002330795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007767658,"about_ca_system_score_gemma":0.00266827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01168494,"about_ca_topic_score_gemma":0.01115343,"domain_scores_codex":[0.9989912,0.0001948558,0.00005052713,0.0002062556,0.0003988192,0.0001583205],"domain_scores_gemma":[0.9976494,0.0006376961,0.0001165154,0.0005819566,0.0008950288,0.0001193185],"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":[0.0007887504,0.0005452341,0.005904291,0.0003593905,0.0001837212,0.0003105064,0.0005167506,0.4657018,0.03483411,0.01437655,0.0208509,0.455628],"study_design_scores_gemma":[0.0001576208,0.00008925189,0.0009722461,0.00002093321,0.00002984655,0.00005334859,0.00005897676,0.9672241,0.013505,0.001772037,0.01607935,0.00003728671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1103647,0.0002286922,0.8196259,0.0003417502,0.0002871898,0.0002899661,0.0007093815,0.04720657,0.02094588],"genre_scores_gemma":[0.1646976,0.0001554103,0.8237197,0.0001320258,0.00005765887,0.000249939,0.001904432,0.004058521,0.005024691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01168494,"threshold_uncertainty_score":0.02416843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471915546934856,"score_gpt":0.2467295452231447,"score_spread":0.2320103897537961,"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."}}