A comparison of two laboratory methods to measure urinary bisphenol A and triclosan in the Canadian Health Measures Survey
Bibliographic record
Abstract
OBJECTIVE: The Canadian Health Measures Survey (CHMS) employed two laboratory methods to measure each of bisphenol A (BPA) and triclosan in urine. This analysis compares method performance. METHODS: Method E-475 used GC-MS/MS to measure BPA in recruitment cycles 1-6 and triclosan in recruitment cycles 2-4. Method E-505 used UPLC-MS/MS for BPA and triclosan in biobanked samples from recruitment cycles 4-6. Using unweighted concentrations for samples available from both methods, and removing observations < LOD (BPA Cycles 4-6, n = 3114 and triclosan Cycle 4, n = 651), we compared E-475 and E-505 with descriptive statistics, scatterplots, and Bland Altman analysis. An E-475 variation using isotope dilution (ID) was performed for triclosan. After applying a model to correct E-475 triclosan for ID (E-475m), we compared modeled results to E-505. RESULTS: The geometric mean (GM) for BPA from E-475 vs. E-505 was 1.2 vs. 1.1 μg/L. The E-475/E-505 GM ratio was 1.03, and the lower-upper limits of agreements (LOA) were 0.59-1.81. The GM for triclosan from E-475 vs. E-505 was 31 vs. 20 μg/L. E-475 concentrations were 1.56 times E-505, and the LOAs were 0.87-2.78. The GM for triclosan from E-475m vs. E-505 was 19 vs. 20 μg/L. E-475m concentrations were 0.93 times E-505, and the LOAs were 0.53-1.64. CONCLUSIONS: BPA concentrations were comparable with E-475 and E-505. Triclosan concentrations were higher with E-475 than E-505. The E-475 triclosan concentrations became comparable to E-505 after correcting for ID. These results will have implications on whether BPA and triclosan data from the two methods can be combined and compared across CHMS recruitment cycles.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".