{"id":"W1997569182","doi":"10.1007/s00477-009-0352-9","title":"Information effect on remediation design of contaminated aquifers using the pump and treat method","year":2009,"lang":"en","type":"article","venue":"Stochastic Environmental Research and Risk Assessment","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Killam Trusts; Ministry of Environment","keywords":"Aquifer; Environmental remediation; Hydraulic conductivity; Extraction (chemistry); Reliability (semiconductor); Environmental science; Computer science; Mathematical optimization; Sampling (signal processing); Soil science; Contamination; Groundwater; Mathematics; Geology; Geotechnical engineering; Power (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001619263,0.0005388429,0.0006890043,0.0007204621,0.0005016726,0.0007650414,0.0006381272,0.0009125277,0.002185154],"category_scores_gemma":[0.007562851,0.0002886725,0.0003895218,0.0004267461,0.000506438,0.001303813,0.0005238836,0.0003423827,0.0002051876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005445933,"about_ca_system_score_gemma":0.0009941425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003276505,"about_ca_topic_score_gemma":0.002786968,"domain_scores_codex":[0.9990251,0.0004621608,0.00003895313,0.0001403097,0.0002158108,0.0001176943],"domain_scores_gemma":[0.9952257,0.003410229,0.0004905586,0.0002919036,0.0005021887,0.00007937081],"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":[0.01361618,0.001044532,0.01739451,0.0004198273,0.0001932988,0.0002739309,0.0001938614,0.5146291,0.1988501,0.01113952,0.00188373,0.2403614],"study_design_scores_gemma":[0.0003579854,0.002585544,0.008763823,0.00001576321,0.0003689951,0.0001421393,0.00009165965,0.7077792,0.274244,0.003768856,0.00178152,0.0001005518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7815543,0.0001729824,0.2127081,0.0004722754,0.0000297617,0.0001094607,0.000197335,0.0009198925,0.003835919],"genre_scores_gemma":[0.9759595,0.00007796037,0.02265129,0.00005736876,0.000008706307,0.00002693352,0.00006891799,0.00003418606,0.001115089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003276505,"threshold_uncertainty_score":0.008563578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02493642706969306,"score_gpt":0.3363590780518669,"score_spread":0.3114226509821739,"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."}}