{"id":"W2791649190","doi":"10.1016/j.epsl.2018.01.007","title":"Imaging the Laguna del Maule Volcanic Field, central Chile using magnetotellurics: Evidence for crustal melt regions laterally-offset from surface vents and lava flows","year":2018,"lang":"en","type":"article","venue":"Earth and Planetary Science Letters","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":90,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Centro de Excelencia en Geotermia de Los Andes; National Science Foundation of Sri Lanka; Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias; Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; National Science Foundation","keywords":"Geology; Magnetotellurics; Volcano; Lava; Andesite; Volcanism; Hydrothermal circulation; Rhyolite; Magma; Petrology; Magma chamber; Geomorphology; Geochemistry; Volcanic rock; Electrical resistivity and conductivity; Seismology; Tectonics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004005971,0.0001832863,0.0001752013,0.00005303789,0.0008017914,0.000229058,0.0003393096,0.00004117789,0.0002152334],"category_scores_gemma":[0.0001237024,0.000126079,0.00004308441,0.0003288278,0.0005368804,0.0005615124,0.00003608636,0.0001978608,0.00002869503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003142309,"about_ca_system_score_gemma":0.0000542846,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009427649,"about_ca_topic_score_gemma":0.001607152,"domain_scores_codex":[0.9982184,0.0001051895,0.000184034,0.0005038864,0.000308698,0.0006797973],"domain_scores_gemma":[0.99867,0.0007574524,0.00006757571,0.0002068733,0.00002811333,0.0002700179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004370698,0.00002719337,0.730633,0.00004572147,0.00003905031,0.00006110318,0.001269282,0.007212552,0.01623819,0.00002635712,0.002445441,0.241565],"study_design_scores_gemma":[0.0001847754,0.0001760698,0.6373048,0.00003389634,0.00002589875,0.00003007935,0.00002837357,0.3592028,0.0004331978,0.0006320478,0.001747719,0.0002003595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914669,0.001119272,0.002010839,0.004501981,0.0004360992,0.0002560884,0.0001436961,0.0000235888,0.00004152897],"genre_scores_gemma":[0.9857037,0.00007440991,0.00886531,0.004876786,0.000380705,4.752718e-7,0.00005410193,0.000003198115,0.00004128194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3519903,"threshold_uncertainty_score":0.9971687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02635652704370987,"score_gpt":0.2492286858956555,"score_spread":0.2228721588519457,"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."}}