{"id":"W1970141731","doi":"10.1016/j.envpol.2006.02.017","title":"An integrated numerical and physical modeling system for an enhanced in situ bioremediation process","year":2006,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Regina","funders":"","keywords":"Bioremediation; Environmental science; Environmental remediation; Groundwater remediation; Process (computing); Numerical modeling; Groundwater; Contamination; Petroleum engineering; Environmental engineering; Geology; Computer science; Geotechnical engineering; Ecology","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":[0.0004343528,0.0007316959,0.0007866338,0.0002368418,0.0005814182,0.0008940281,0.001388363,0.001021408,0.002699947],"category_scores_gemma":[0.0009118415,0.000441233,0.0004268891,0.0002149515,0.0003280356,0.0009041124,0.0008572858,0.0007044698,0.0004763669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006797279,"about_ca_system_score_gemma":0.00118246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00511271,"about_ca_topic_score_gemma":0.004199428,"domain_scores_codex":[0.9997917,0.00003938571,0.00002113284,0.00005635709,0.00007638302,0.00001515095],"domain_scores_gemma":[0.9996673,0.0001100077,0.00003527367,0.00005612562,0.00009965232,0.00003164071],"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":[0.0002390204,0.000416121,0.00218862,0.00009443318,0.00005409504,0.0001354752,0.0001552817,0.8618912,0.09587092,0.002822766,0.0008690805,0.03526295],"study_design_scores_gemma":[0.00001727701,0.00003029209,0.0001370644,0.000001547587,0.00000936826,0.00001109765,0.000005101806,0.9916797,0.007199327,0.0001908944,0.0007106039,0.000007637609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.134068,0.00009574309,0.8551067,0.0002694719,0.0001088234,0.0001859272,0.0003216654,0.005887015,0.003956717],"genre_scores_gemma":[0.6943782,0.0001822611,0.2991214,0.0001127165,0.00003924378,0.0004555287,0.0005021114,0.0002548409,0.004953723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00511271,"threshold_uncertainty_score":0.01016587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007228308976849857,"score_gpt":0.2232728304400775,"score_spread":0.2160445214632277,"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."}}