{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003257788,0.0007388445,0.0003914879,0.00238631,0.0002835293,0.001465679,0.001000806,0.001146533,0.001388253],"category_scores_gemma":[0.004855477,0.0002568962,0.0002816963,0.001425257,0.001435445,0.002797052,0.0006411316,0.000408814,0.000243241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001340703,"about_ca_system_score_gemma":0.0005823669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004871583,"about_ca_topic_score_gemma":0.004988135,"domain_scores_codex":[0.9993749,0.0002384936,0.00002996901,0.00009357704,0.0002375792,0.00002543681],"domain_scores_gemma":[0.9954643,0.002717421,0.000356205,0.0003410718,0.001046381,0.00007462162],"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":[0.0004536657,0.0005253132,0.05667954,0.000633681,0.0001055793,0.0003542195,0.0002745556,0.4900247,0.04872108,0.03423763,0.001624398,0.3663657],"study_design_scores_gemma":[0.00001727875,0.0001982751,0.01903872,0.0001003949,0.00004016843,0.0001104297,0.0002896922,0.937622,0.03183533,0.008136371,0.002553042,0.00005828065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6244419,0.00377941,0.3429408,0.002030018,0.00004170054,0.0001536719,0.001015846,0.0005294893,0.02506715],"genre_scores_gemma":[0.9638027,0.001509868,0.03355874,0.00005304315,0.00001809664,0.00004287089,0.0002309961,0.00003475398,0.0007488395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004871583,"threshold_uncertainty_score":0.01722902,"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."}}