{"id":"W4242977585","doi":"10.4133/1.2923658","title":"Delineation of Water Inflow in an Underground Potash Mine with 3‐D Electrical Resistivity Imaging","year":2006,"lang":"en","type":"article","venue":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2006","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"PotashCorp (Canada); Golder Associates (Canada); University of British Columbia","funders":"","keywords":"Potash; Inflow; Borehole; Mining engineering; Geology; Electrical resistivity and conductivity; Inversion (geology); Electrical resistivity tomography; Aquifer; Drilling; Resistive touchscreen; Groundwater; Ground-penetrating radar; Geotechnical engineering; Engineering; Structural basin; Electrical engineering; Geomorphology; Materials science; Mechanical engineering; Radar","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":[0.0001396924,0.0002663796,0.0001909054,0.0006222821,0.0001688605,0.0003940276,0.0002569729,0.0004460897,0.0002929433],"category_scores_gemma":[0.0005960032,0.0002798063,0.0002648965,0.0003969426,0.0003650857,0.000368786,0.0005209322,0.0002152488,0.0000758871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002944997,"about_ca_system_score_gemma":0.0003581552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005535548,"about_ca_topic_score_gemma":0.01006994,"domain_scores_codex":[0.9999322,0.00001182645,0.000005280416,0.0000170358,0.0000214622,0.00001228563],"domain_scores_gemma":[0.9998316,0.00008093144,0.0000274586,0.00001672746,0.00002895121,0.00001434655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007568073,0.0001741574,0.1491764,0.0002388533,0.00007399442,0.004696861,0.001857414,0.4291759,0.2853898,0.00217307,0.0007541175,0.1255326],"study_design_scores_gemma":[0.00004571021,0.0001211113,0.06177684,0.0000337118,0.0000372475,0.0007811665,0.000421454,0.8959635,0.03851857,0.001455141,0.0007843974,0.00006114486],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9520739,0.0000497538,0.04571344,0.0001039684,0.00000483674,0.00002868456,0.0001880804,0.0002504039,0.001586949],"genre_scores_gemma":[0.9801086,0.0000456017,0.01948525,0.00001013778,0.000001570146,0.000009528438,0.00007694646,0.00000531998,0.0002571831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005535548,"threshold_uncertainty_score":0.01100665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003546360149053896,"score_gpt":0.1700784957563967,"score_spread":0.1665321356073428,"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."}}