{"id":"W2052603996","doi":"10.1520/gtj101058","title":"Interpreting Slug Tests with Large Data Sets","year":2009,"lang":"en","type":"article","venue":"Geotechnical Testing Journal","topic":"Water Systems and Optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Graph; Mathematics; Hydraulic conductivity; Algorithm; Data point; Statistics; Linearity; Data mining; Computer science; Soil science; Combinatorics; Geology; Engineering; Soil water","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":[0.00670818,0.001061536,0.001070382,0.003471953,0.0005735303,0.001813675,0.001188735,0.001095266,0.001343317],"category_scores_gemma":[0.03805095,0.0004429446,0.0006269927,0.00276347,0.0008272475,0.001185554,0.001202178,0.0008444654,0.0007171261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006065319,"about_ca_system_score_gemma":0.0004514722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002873603,"about_ca_topic_score_gemma":0.00320602,"domain_scores_codex":[0.9954162,0.00167615,0.0005696577,0.0005575075,0.001610456,0.0001699901],"domain_scores_gemma":[0.9625457,0.02583472,0.002794518,0.003977838,0.004494779,0.0003524601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002162449,0.0008991456,0.2780927,0.001483605,0.0007940212,0.005471139,0.002964785,0.2361166,0.1183186,0.003123768,0.01057526,0.3399979],"study_design_scores_gemma":[0.0001237669,0.001301829,0.1840643,0.0002561937,0.0002375618,0.001754862,0.002999993,0.6556582,0.123125,0.01712202,0.01298967,0.0003665585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7039154,0.0004236311,0.2851829,0.0003703348,0.0002226927,0.0003502638,0.002624333,0.004482291,0.002428195],"genre_scores_gemma":[0.8873446,0.0001757448,0.109261,0.0001457023,0.00005994415,0.0001651192,0.001963942,0.0003966906,0.0004872121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00670818,"threshold_uncertainty_score":0.03547662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0320011581602609,"score_gpt":0.2556356899522327,"score_spread":0.2236345317919718,"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."}}