{"id":"W2037652296","doi":"10.1007/s10596-013-9389-4","title":"A reduced-order model for Monte Carlo simulations of stochastic groundwater flow","year":2013,"lang":"en","type":"article","venue":"Computational Geosciences","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec; Institut National de la Recherche Scientifique","funders":"","keywords":"Monte Carlo method; Mathematical optimization; Basis function; Hydrogeology; Basis (linear algebra); Partial differential equation; Context (archaeology); Applied mathematics; Hydraulic head; Mathematics; Groundwater flow; Groundwater model; Logarithm; Algorithm; Aquifer; Groundwater; Mathematical analysis; Statistics; Geometry","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":[0.0006660488,0.0004770485,0.001458424,0.0006435341,0.000722322,0.001130525,0.002262121,0.001948134,0.00229131],"category_scores_gemma":[0.003968764,0.0007401056,0.0009901748,0.0007876036,0.001021464,0.001372021,0.000926218,0.001654945,0.0004663181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493119,"about_ca_system_score_gemma":0.001812122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02557791,"about_ca_topic_score_gemma":0.01883408,"domain_scores_codex":[0.9996538,0.0001406035,0.00001826337,0.0000424696,0.0001087791,0.00003603922],"domain_scores_gemma":[0.9989622,0.0005771627,0.00008678147,0.0001103837,0.0001877539,0.0000756985],"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":[0.000009615913,0.000009825912,0.00007383715,0.00000772891,0.000007567429,0.00001015927,0.000008744782,0.9896923,0.0001801149,0.008818586,0.0001489043,0.001032661],"study_design_scores_gemma":[0.00000188,9.631862e-7,0.00001052094,5.123948e-7,0.000001078466,0.000001054903,4.991405e-7,0.9981542,0.0000249839,0.001735298,0.00006781821,0.000001116752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04866609,0.0004522981,0.9405596,0.000739803,0.000120265,0.00006323698,0.0003984638,0.0006595858,0.008340674],"genre_scores_gemma":[0.8329114,0.000595856,0.1542502,0.0002865038,0.0001639894,0.0004130851,0.0006897781,0.0003894863,0.01029961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02557791,"threshold_uncertainty_score":0.05085802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02920623071662178,"score_gpt":0.2759414638167528,"score_spread":0.246735233100131,"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."}}