{"id":"W2184196447","doi":"10.1007/s10040-012-0858-y","title":"Estimating regional-scale fractured bedrock hydraulic conductivity using discrete fracture network (DFN) modeling","year":2012,"lang":"en","type":"article","venue":"Hydrogeology Journal","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Ministry of Environment","keywords":"Lineament; Geology; Bedrock; Hydraulic conductivity; Aquifer; Outcrop; Hydrogeology; Fracture (geology); Fault (geology); Geomorphology; Scale (ratio); Groundwater; Geotechnical engineering; Hydrology (agriculture); Soil science; Seismology; Tectonics; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005795227,0.0005334332,0.0005865842,0.000793393,0.0004864418,0.0005262119,0.001054633,0.0008732508,0.0004380349],"category_scores_gemma":[0.0018238,0.0006142225,0.0007899489,0.0009777541,0.0004208832,0.000810229,0.0003496969,0.0004137257,0.0001056859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00181828,"about_ca_system_score_gemma":0.0014695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.117136,"about_ca_topic_score_gemma":0.1142389,"domain_scores_codex":[0.999821,0.00004051281,0.00001190712,0.00006495592,0.00003476886,0.00002683508],"domain_scores_gemma":[0.9992047,0.0004494074,0.0000842125,0.00007662613,0.0001407377,0.00004424262],"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":[0.00002995429,0.00003607916,0.01239054,0.00001031878,0.00002802221,0.00003274392,0.00002068464,0.9808326,0.00106228,0.0001999673,0.00007178057,0.005285059],"study_design_scores_gemma":[0.000005811254,0.000005438621,0.002150479,9.179615e-7,0.000005523802,0.000005572034,0.000005538351,0.9974602,0.0002203607,0.0001098612,0.00002591379,0.000004313074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9679481,0.00006564802,0.03019787,0.00007045174,0.000008368582,0.00001535383,0.0005585102,0.0003261843,0.0008094024],"genre_scores_gemma":[0.9872689,0.00002851241,0.01228216,0.000004355979,0.000002937388,0.00001024939,0.0002288738,0.00001280325,0.0001610689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.117136,"threshold_uncertainty_score":0.2329082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02645306539681104,"score_gpt":0.2659019165492967,"score_spread":0.2394488511524857,"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."}}