{"id":"W3160092837","doi":"10.5194/egusphere-egu2020-9025","title":"On the use of the ground water fluxes for hydraulic tomography: Theoretical and field-based assessments","year":2020,"lang":"en","type":"article","venue":"","topic":"Flow Measurement and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Hydraulic conductivity; Aquifer; Groundwater; Groundwater flow; Groundwater model; Geology; Soil science; Hydraulic head; Tomography; Slug test; Thermal conduction; Geotechnical engineering; Hydrology (agriculture); Environmental science; Materials science; Optics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006895752,0.00006784384,0.0000792728,0.00001549291,0.0000396111,0.00003404663,0.00008453658,0.00002464507,0.000189614],"category_scores_gemma":[0.0000288185,0.00002772515,0.00009140151,0.0000654877,0.00003726897,0.00003217123,0.00001281777,0.00005380434,0.000001414397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002806071,"about_ca_system_score_gemma":0.000001978743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006540313,"about_ca_topic_score_gemma":0.000003346634,"domain_scores_codex":[0.9996168,0.0000199414,0.00008532593,0.00007105112,0.0001146222,0.00009225497],"domain_scores_gemma":[0.9996456,0.0001978891,0.000006236854,0.0001123469,0.00001438554,0.00002357844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005567252,0.000384765,0.03688132,0.001016604,0.002990254,0.00000441716,0.001902585,0.1063673,0.347178,0.3799712,0.1085731,0.0141737],"study_design_scores_gemma":[0.0004250603,0.0001684947,0.0006327235,0.00002461709,0.0001399432,8.707969e-8,0.00004179101,0.6809158,0.3104129,0.002766783,0.004329427,0.0001424129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694201,0.00001386933,0.0215447,0.00764246,0.00005404857,0.0002145537,0.000003717214,0.00004656434,0.001060009],"genre_scores_gemma":[0.9974281,0.000001836712,0.0002362567,0.002273152,0.0000187278,0.00001102158,0.000001907343,0.000007572492,0.00002141464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5745485,"threshold_uncertainty_score":0.207614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03672749394039375,"score_gpt":0.2276805011324408,"score_spread":0.1909530071920471,"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."}}