Uranium Immobilization in an Iron-Rich Rhizosphere of a Native Wetland Plant from the Savannah River Site under Reducing Conditions
Bibliographic record
Abstract
The hypothesis of this study was that iron plaques formed on the roots of wetland plants and their rhizospheres create environmental conditions favorable for iron reducing bacteria that promote the in situ immobilization of uranium. Greenhouse microcosm studies were conducted using native plants (Sparganium americanum) from a wetland located on the Savannah River Site, Aiken, SC. After iron plaques were established during a 73-day period by using an anoxic Fe(II)-rich nutrient solution, a U(VI) amended nutrient solution was added to the system for an additional two months. Compared to plant-free control microcosms, microcosms containing iron plaques successfully stimulated the growth of targeted iron reducing bacteria, Geobacter spp. Their population continuously increased after the introduction of the U(VI) nutrient solution. The reduction of some of the U(VI) to U(IV) by iron reducing bacteria was deduced based on the observations that the aqueous Fe(II) concentrations increased while the U(VI) concentrations decreased. The Fe(II) produced by the iron reducing bacteria was assumed to be reoxidized by the oxygen released from the roots. Advanced spectroscopic analyses revealed that a significant fraction of the U(VI) had been reduced to U(IV) and they were commonly deposited in association with phosphorus on the iron plaque.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".