Solid phase extraction of large volume of water and beverage samples to improve detection limits for GC-MS analysis of bisphenol A and four other bisphenols
Bibliographic record
Abstract
Solid phase extraction (SPE) of large volumes of water and beverage products was investigated for the GC-MS analysis of bisphenol A (BPA), bisphenol AF (BPAF), bisphenol F (BPF), bisphenol E (BPE), and bisphenol B (BPB). While absolute recoveries of the method were improved for water and some beverage products (e.g. diet cola, iced tea), breakthrough may also have occurred during SPE of 200 mL of other beverages (e.g. BPF in cola). Improvements in method detection limits were observed with the analysis of large sample volumes for all bisphenols at ppt (pg/g) to sub-ppt levels. This improvement was found to be proportional to sample volumes for water and beverage products with less interferences and noise levels around the analytes. Matrix effects and interferences were observed during SPE of larger volumes (100 and 200 mL) of the beverage products, and affected the accurate analysis of BPF. This improved method was used to analyse bisphenols in various beverage samples, and only BPA was detected, with levels ranging from 0.022 to 0.030 ng/g for products in PET bottles, and 0.085 to 0.32 ng/g for products in cans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".