Capillary electrophoresis and liquid chromatography-mass spectrometry analysis of Bisphenol A (BPA) in environmental waters
Bibliographic record
Abstract
Bisphenol A (BPA) and its structural analogues (BPF, BPS, BPP, BPZ, BADGE, BPAF, BPAP) are used in the production of polycarbonate plastics and epoxy resins. Most of them have proven endocrine disruptive effects in humans and in other life forms in very low concentrations. BPA is of particular interest as it is mass produced and released into the environment as a result of human activity and accumulates in aquatic and terrestrial environments. Recent studies have revealed the presence of BPA in fresh water resources which is not only a threat to the fresh water ecosystems but also to humans because the usual source of drinking water is from rivers and streams. Presence of bisphenols in the environment is crucial and use of analytical techniques for their chemical separation and subsequent analysis is necessary for efficient environmental monitoring of these compounds. This study used capillary electrophoresis (CE) and liquid chromatography-mass spectrometry (LC/MS) to develop sensitive analytical protocols for quantification of BPA present in environmental, swimming pool and tap water samples from the Kamloops region. Standard addition and internal standard calibration approaches were used to quantify BPA in the water samples. In addition, a CE method was developed to simultaneously separate eight bisphenol analogues, BPA, BPF, BPS, BPZ, BPP, BPAP, BPAF and BADGE. Optimization of experimental parameters such as pH, buffer concentration, detection wavelength, applied voltage and buffer additives enabled the successful baseline separation of all the analogues.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".