Trichloroacetic acid as a biomarker of exposure to disinfection by-products in drinking water: a human exposure trial in Adelaide, Australia.
Bibliographic record
Abstract
We addressed the need for a biomarker of ingestion exposure to drinking water disinfection by-products by performing a human exposure trial. We evaluated urinary excretion of trichloroacetic acid (TCAA) as an exposure biomarker using 10 volunteers who normally consume their domestic tap water. We recruited the volunteers at a water quality research laboratory in Adelaide, Australia. Participants maintained a detailed consumption and exposure diary over the 5-week study. We also analyzed tap water and first morning urine (FMU) samples for TCAA, and tap water for chloral hydrate (CH). We documented both interindividual and intraindividual variability in TCAA ingestion and urinary excretion, and both were substantial. With a TCAA-free bottled water intervention, we used creatinine-adjusted urinary TCAA levels to estimate urinary TCAA excretion half-lives for three of the participants. We observed correspondence over time between estimated TCAA excretion, calculated from TCAA + CH ingestion levels, and measured TCAA urinary excretion. This study demonstrates the merits and feasibility of using TCAA in FMU as an exposure biomarker, and reveals remaining concerns about possible alternate sources of TCAA exposure for individuals with low drinking water ingestion exposure.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".