Uranium Isotope Fractionation during Adsorption, (Co)precipitation, and Biotic Reduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Uranium contamination of surface environments is a problem associated with both U-ore extraction/processing and situations in which groundwater comes into contact with geological formations high in uranium. Apart from the environmental concerns about U contamination, its accumulation and isotope composition have been used in marine sediments as a paleoproxy of the Earth’s oxygenation history. Understanding U isotope geochemistry is then essential either to develop sustainable remediation procedures as well as for use in paleotracer applications. We report on parameters controlling U immobilization and U isotope fractionation by adsorption onto Mn/Fe oxides, precipitation with phosphate, and biotic reduction. The light U isotope ( 235 U) is preferentially adsorbed on Mn/Fe oxides in an oxic system. When adsorbed onto Mn/Fe oxides, dissolved organic carbon and carbonate are the most efficient ligands limiting U binding resulting in slight differences in U isotope composition (δ 238 U = 0.22 ± 0.06‰) compared to the DOC/DIC-free configuration (δ 238 U = 0.39 ± 0.04‰). Uranium precipitation with phosphate does not induce isotope fractionation. In contrast, during U biotic reduction, the heavy U isotope ( 238 U) is accumulated in reduced species (δ 238 U up to −1‰). The different trends of U isotope fractionation in oxic and anoxic environments makes its isotope composition a useful tracer for both environmental and paleogeochemical applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it