{"id":"W2326349243","doi":"10.1190/segam2015-5848713.1","title":"3D joint inversion of magnetotelluric and magnetovariational data to image conductive anomalies in Southern Alberta, Canada","year":2015,"lang":"en","type":"article","venue":"","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Magnetotellurics; Inversion (geology); Electrical impedance; Electrical conductor; Geology; Inverse problem; Electrical resistivity tomography; Seismology; Geophysics; Geodesy; Electrical resistivity and conductivity; Engineering; Mathematics; Electrical engineering; Mathematical analysis; Tectonics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002173964,0.00007642743,0.000145856,0.00005051737,0.00001957034,0.00001220597,0.0001446064,0.00002563376,0.0009080985],"category_scores_gemma":[0.0002606597,0.00005646588,0.000007236776,0.0002655126,0.0000370399,0.0001345305,0.0000496322,0.00006320151,0.00005723227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005374695,"about_ca_system_score_gemma":0.0001959643,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9695542,"about_ca_topic_score_gemma":0.9328249,"domain_scores_codex":[0.9991911,0.00008525482,0.0001498768,0.0002174653,0.0002005114,0.0001558103],"domain_scores_gemma":[0.9993975,0.0002053642,0.00003341723,0.0001482273,0.00004568084,0.0001698057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007477877,0.0001792874,0.2430435,0.0001036954,0.00005970786,0.0000606283,0.004971827,0.003712058,0.00171515,0.0009047682,0.01465983,0.7298417],"study_design_scores_gemma":[0.0005944971,0.0004815079,0.8673407,0.000008789976,0.00001492506,0.00000615966,0.001549917,0.1218662,0.0002926824,0.004477446,0.003088197,0.0002790458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905745,0.00008049813,0.0003029162,0.00137334,0.00008108412,0.0001209247,0.0001803657,0.000004106268,0.007282269],"genre_scores_gemma":[0.9648207,0.000001564225,0.03187317,0.0004041381,0.00002948877,3.502958e-7,0.0001113036,0.000001497571,0.002757759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7295627,"threshold_uncertainty_score":0.9943042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04603900498579731,"score_gpt":0.2312478770941296,"score_spread":0.1852088721083323,"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."}}