Effect of sodium dithionite on the surface composition of iron‐containing aquifer sediment
Bibliographic record
Abstract
Abstract AES, XPS and SIMS analyses were used to characterize the surface of Pantex aquifer sediment under pretreatment conditions previously shown to activate the sediment for remediation of the explosives‐contaminated aquifer. The untreated sediment contains detectable concentrations of iron, but the composition is heterogeneous and the nature of the iron at the surface is poorly defined. Treatment with dithionite (Na 2 S 2 O 4 ) produced Fe 3 O 4 ‐like material, as evidenced by characteristic Fe 2p XPS structure. Sediment treated with buffered dithionite (pH = 8.8) shows a higher Fe 2+ /Fe 3+ ratio and retains strongly adsorbed FeS‐like surface species even after copious washing with deionized water. The negative SIMS data indicate that, in the absence of the K 2 CO 3 buffer, the dithionite treatment places relatively little sulfur onto the surface, but requires the higher buffered pH to form sulfide and sulfates. Detection of Fe 3 O 4 and FeS on the sediment surface after dithionite treatment supports the effectiveness of this treatment in remediating contaminated aquifer sediment. SIMS and XPS indicate that treating with buffered dithionite also results in some loss of iron from the sediment surface. Copyright © 2009 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".