Method variables affecting the bioaccessibility of arsenic in soil
Bibliographic record
Abstract
Arsenic bioaccessibility tests are now being commonly used in risk assessment. However, concerns remain about the reliability of such tests because the bioaccessibility of arsenic from soil may be susceptible to soil composition (including iron concentration), as well as method considerations such as varying liquid-to-solid ratios and the chosen buffer system. In this study, arsenic-contaminated tailings and soils were tested to compare two bioaccessibility methods: one that uses glycine as a buffer, and a second that is more physiologically based. With the glycine-buffered method, arsenic and iron bioaccessibility increased in the presence of a higher buffer concentration at higher liquid-to-solid ratios, whereas the results of physiologically-based tests were unaffected by variations in these parameters. In the glycine-buffered system, interactions between iron and glycine may influence the concentration of arsenic in solution, which may not be consistent with human gastrointestinal conditions. The choice of a physiologically-based method may be more appropriate to achieve representative arsenic bioaccessibility values toward estimating risks to human health.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".