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Record W7008419125

Capillary electrophoresis and liquid chromatography-mass spectrometry analysis of Bisphenol A (BPA) in environmental waters

2015· article· en· W7008419125 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
Fundersnot available
KeywordsBisphenol ACapillary electrophoresisTap waterBisphenolMass spectrometryAquatic environmentAquatic ecosystemPolycarbonateCapillary actionEndocrine disruptor
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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.

Opus teacher head0.003
GPT teacher head0.208
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueArca (British Columbia Electronic Library Network)Same topicEffects and risks of endocrine disrupting chemicalsFrench-language works237,207