{"id":"W2082007807","doi":"10.1016/j.jenvrad.2013.10.017","title":"Retention and chemical speciation of uranium in an oxidized wetland sediment from the Savannah River Site","year":2013,"lang":"en","type":"article","venue":"Journal of Environmental Radioactivity","topic":"Radioactive element chemistry and processing","field":"Chemistry","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Light Source (Canada); University of Saskatchewan; University of Guelph","funders":"Argonne National Laboratory; U.S. Department of Energy; U.S. Environmental Protection Agency; Princeton University; Office of Science; Savannah River National Laboratory; Canadian Light Source","keywords":"Uranium; Sorption; Chemistry; Environmental chemistry; Uranyl; Sediment; Organic matter; Genetic algorithm; Extraction (chemistry); XANES; Dissolution; Geology; Spectroscopy; Adsorption; Ecology","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":[0.0000569972,0.0001223646,0.0001490505,0.0004745036,0.0005407414,0.0003378739,0.0002570697,0.000244723,0.000667532],"category_scores_gemma":[0.00009991479,0.0001324343,0.0001111449,0.000228122,0.0002118615,0.0001609158,0.0001936307,0.0001402222,0.0001405334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002399372,"about_ca_system_score_gemma":0.0002902903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0254166,"about_ca_topic_score_gemma":0.03204839,"domain_scores_codex":[0.9999646,0.000003273524,0.000002430856,0.00000916714,0.000009891701,0.00001063973],"domain_scores_gemma":[0.9999599,0.000006461569,0.000006372169,0.000002067861,0.00001435474,0.00001093561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001163273,0.0002574163,0.3058298,0.00008539225,0.0000766091,0.001291083,0.001364669,0.0008150152,0.674328,0.0001616241,0.00017404,0.0144531],"study_design_scores_gemma":[0.00001822823,0.0003006954,0.9553463,0.000006787659,0.00003533368,0.0004916741,0.001231338,0.001786812,0.03987515,0.0000567625,0.0008388842,0.0000121029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997998,0.00001052513,0.00003394957,0.000002178502,5.608929e-7,7.761055e-7,0.00002244919,0.000002057054,0.0001278235],"genre_scores_gemma":[0.9993064,0.00001964707,0.0001045643,0.000002910898,8.318423e-7,0.000001088744,0.00008177385,0.000001978902,0.0004808331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0254166,"threshold_uncertainty_score":0.05053735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009072433443872253,"score_gpt":0.2075884475606548,"score_spread":0.1985160141167826,"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."}}