Variability of bioaccessibility results using seventeen different methods on a standard reference material, NIST 2710
Bibliographic record
Abstract
Bioaccessibility is a measurement of a substance's solubility in the human gastro-intestinal system, and is often used in the risk assessment of soils. The present study was designed to determine the variability among laboratories using different methods to measure the bioaccessibility of 24 inorganic contaminants in one standardized soil sample, the standard reference material NIST 2710. Fourteen laboratories used a total of 17 bioaccessibility extraction methods. The variability between methods was assessed by calculating the reproducibility relative standard deviations (RSDs), where reproducibility is the sum of within-laboratory and between-laboratory variability. Whereas within-laboratory repeatability was usually better than (<) 15% for most elements, reproducibility RSDs were much higher, indicating more variability, although for many elements they were comparable to typical uncertainties (e.g., 30% in commercial laboratories). For five trace elements of interest, reproducibility RSDs were: arsenic (As), 22-44%; cadmium (Cd), 11-41%; Cu, 15-30%; lead (Pb), 45-83%; and Zn, 18-56%. Only one method variable, pH, was found to correlate significantly with bioaccessibility for aluminum (Al), Cd, copper (Cu), manganese (Mn), Pb and zinc (Zn) but other method variables could not be examined systematically because of the study design. When bioaccessibility results were directly compared with bioavailability results for As (swine and mouse) and Pb (swine), four methods returned results within uncertainty ranges for both elements: two that were defined as simpler (gastric phase only, limited chemicals) and two were more complex (gastric + intestinal phases, with a mixture of chemicals).
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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 | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".