Comparison of Two <i>In Vitro</i> Extraction Protocols for Assessing Metals’ Bioaccessibility Using Dust and Soil Reference Materials
Bibliographic record
Abstract
The bioaccessibility of arsenic, cadmium, chromium, copper, lead, nickel, and zinc in four National Institute of Standards and Technology (NIST) standard reference materials and two Canadian dust samples as determined using the Solubility/Bioavailability Research Consortium (SBRC) in vitro procedure ranged from a low of 1.8% for chromium in standard reference material NIST 2711 to a high of 95.2% for cadmium in NIST 2584. The SBRC data were compared to data generated using a modified EN-71 Toy Safety protocol conducted at two different laboratories. Results for the two extraction methods compared well with differences between the means (SBRC vs. modified EN-71) generally less than 10% for the majority of the metals. These differences between the two extraction methods were negligible compared to variability caused by (a) the inherent heterogeneity of typical house dust samples and (b) differences in ICP-MS analytical approaches employed in the different laboratories. Results indicate that the modified EN-71 method is useful and appropriate as a relatively simple, rapid, and reproducible screening test for estimating metals’ bioaccessibility in soil and dust samples.
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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 | 0.004 | 0.007 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".