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Record W2069748217 · doi:10.1039/b800861b

On-line solid phase extraction and liquid chromatography/tandem mass spectrometry to quantify pharmaceuticals, pesticides and some metabolites in wastewaters, drinking, and surface waters

2008· article· en· W2069748217 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Monitoring · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsNatural Sciences and Engineering Research CouncilPolytechnique MontréalUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChromatographyChemistrySolid phase extractionSample preparationElectrosprayLiquid chromatography–mass spectrometryExtraction (chemistry)WastewaterTandem mass spectrometryMass spectrometryDetection limit

Abstract

fetched live from OpenAlex

A simple on-line method was developed for the analysis of pharmaceuticals, pesticides and some metabolites in drinking, surface and wastewater samples. The technique is based on the use of on-line solid-phase extraction combined with liquid chromatography electrospray tandem mass spectrometry with positive electrospray ionization (LC-ESI(PI)-MS/MS). The injection of only 1 mL of filtered water sample is used with a total analysis time of 20 min, including the period required to flush the SPE cartridge with organic solvent and reconditioning the LC column. Method detection limits were in the range of 2 to 24 ng L(-1) for the compounds of interest, with recoveries from 87 to 110% in surface as well as wastewater samples. Matrix effects were observed for some compounds without exceeding more than 25%. All results displayed a good degree of reproducibility, with relative standard deviations (RSD) of less than 12% for all compounds. Moreover, at least 200 samples were analyzed without altering the performance of the pre-concentration column. This method was preferred over traditional off-line procedures because it minimizes tedious sample preparation, increases productivity and sample throughput. The analysis of various water and wastewater samples showed that caffeine, carbamazepine and atrazine could be detected in all the samples analysed and the selected compounds are always present in at least one of the sample types.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.343
Teacher spread0.305 · 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