{"id":"W4405323963","doi":"10.5194/egusphere-2024-3787","title":"Explicit simulation of reactive microbial transport with a dual-permeability, two-site kinetic deposition formulation using the integrated surface-subsurface hydrological model HydroGeoSphere (rev. 2699)","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Geological Survey of Canada","funders":"Sentinelle Nord, Université Laval; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"TRACER; Groundwater; Permeability (electromagnetism); Aquifer; Environmental science; Deposition (geology); Wellhead; Surface water; Subsurface flow; Water transport; Hydrology (agriculture); Soil science; Chemistry; Geology; Environmental engineering; Water flow; Geotechnical engineering; Petroleum engineering; Membrane; Sediment; Geomorphology","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":[0.0002769466,0.0004763694,0.0004882363,0.0002317938,0.0004083003,0.0006735079,0.001067493,0.001353919,0.002392197],"category_scores_gemma":[0.0006371444,0.0003627604,0.0006741986,0.0003356329,0.0005516872,0.0004541719,0.0008167649,0.0008304838,0.0002112757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008896408,"about_ca_system_score_gemma":0.00140397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02600978,"about_ca_topic_score_gemma":0.01501531,"domain_scores_codex":[0.9999028,0.00002577226,0.000004800255,0.00001726889,0.00002377842,0.00002566386],"domain_scores_gemma":[0.999731,0.000131897,0.00002757376,0.00001962365,0.00004879897,0.00004118285],"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":[0.00002604121,0.00003566966,0.0009255567,0.00002177822,0.00001254816,0.00004862838,0.00002103809,0.9933408,0.002158297,0.001937547,0.0001869739,0.001285168],"study_design_scores_gemma":[0.00001351643,0.00001014094,0.000130775,0.000001639682,0.000002602213,0.000004671233,0.000007229465,0.9990702,0.0002917699,0.0002227583,0.0002416151,0.000002962971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7740269,0.0003336802,0.1937218,0.0007237105,0.0001854387,0.0002645156,0.002606829,0.0009368412,0.02720035],"genre_scores_gemma":[0.9644684,0.0001458241,0.03028535,0.00009634367,0.00002453847,0.0002037066,0.0006784286,0.0001017583,0.003995738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02600978,"threshold_uncertainty_score":0.05171674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02294125573053287,"score_gpt":0.2547020301568796,"score_spread":0.2317607744263467,"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."}}