Derivation of biomonitoring equivalent for inorganic tin for interpreting population-level urinary biomonitoring data
Bibliographic record
Abstract
Population-level biomonitoring of tin in urine has been conducted by the U.S. National Health and Nutrition Examination Survey (NHANES) and the National Nutrition and Health Study (ENNS - Étude nationale nutrition santé) in France. The general population is predominantly exposed to inorganic tin from the consumption of canned food and beverages. The National Institute for Public Health and the Environment of the Netherlands (RIVM) has established a tolerable daily intake (TDI) for chronic exposure to inorganic tin based on a NOAEL of 20 mg/kg bw per day from a 2-year feeding study in rats. Using a urinary excretion fraction (0.25%) from a controlled human study along with a TDI value of 0.2 mg/kg bw per day, a Biomonitoring Equivalent (BE) was derived for urinary tin (26 μg/g creatinine or 20 μg/L urine). The geometric mean and the 95th percentile tin urine concentrations of the general population in U.S. (0.705 and 4.5 μg/g creatinine) and France (0.51 and 2.28 μg/g creatinine) are below the BE associated with the TDI, indicating that the population exposure to inorganic tin is below the exposure guidance value of 0.2 mg/kg bw per day. Overall, the robustness of pharmacokinetic data forming the basis of the urinary BE development is medium. The availability of internal dose and kinetic data in the animal species forming the basis of the assessment could improve the overall confidence in the present assessment.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".