Lead and Arsenic Bioaccessibility and Speciation as a Function of Soil Particle Size
Bibliographic record
Abstract
Bioavailability research of soil metals has advanced considerably from default values to validated in vitro bioaccessibility (IVBA) assays for site-specific risk assessment. Previously, USEPA determined that the soil-size fraction representative of dermal adherence and consequent soil ingestion was <250 μm. This size fraction was widely used in testing efforts for both in vivo and in vitro experiments. However, recent studies indicate the <150-μm size fraction better represents the particle size that adheres to skin for potential ingestion. At issue is the relevance of validated in vivo and in vitro methods developed with <250 μm moving to the <150-μm fraction. The objectives of this study were to investigate <250-μm versus <150-μm particle size and particle size groups for evaluating lead (Pb) and arsenic (As) IVBA and speciation. Soils with different properties were homogenized, oven dried, and sieved: <250 to > 150, <150 to >75, <75 to >38, and <38 μm. Sieved versus ground subsamples of <250-μm and <150-μm bulk soils were also used for IVBA and synchrotron-based Pb and As speciation. Although we observed an increase in total and IVBA-extractable Pb and As with decreased soil particle size, changes in %IVBA of Pb and As (dependent on the ratio extractable:total) remained consistent in all of the tested soils. No significant changes in Pb and As speciation were observed across the soil fractions. The results suggest that using the more relevant <150-μm fraction will not undermine currently validated IVBA protocols in future bioavailability studies.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".