MétaCan
Menu
Back to cohort
Record W2050224978 · doi:10.1080/03067310410001729600

Determination of acephate and its degradation product methamidophos in soil and water by solid-phase extraction (SPE) and GC-MS

2004· article· en· W2050224978 on OpenAlexaffabout
Annick D. St-Amand, Louise Girard

Bibliographic record

VenueInternational Journal of Environmental & Analytical Chemistry · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Residue Analysis and Safety
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMethamidophosSolid phase extractionAcephateExtraction (chemistry)ElutionChromatographyChemistryMatrix (chemical analysis)PesticideEnvironmental chemistry

Abstract

fetched live from OpenAlex

Abstract Acephate and its metabolite, methamidophos, are both highly polar organophosphorus pesticides (OPs) and are therefore highly soluble in water, which leads to difficulties when traditional methods of extraction, such as LLE (liquid–liquid extraction), are used. Solid-phase extraction (SPE) is a relatively new, highly versatile method, which has proven successful in many cases that were considered problematic in the past. In this study, several adsorbents (polymeric and silica based) and parameters are considered and modified to obtain maximum recovery. Maximum recoveries for acephate and methamidophos were found to be 90–95% and 85–90% respectively with Oasis HLB cartridges and methylene chloride as the elution solvent. In order to establish applicability and reliability, the matrix effect of several real water and solid (compost and soil) samples was evaluated. A 20–30% diminution of recovery is noted for some samples with a complex matrix containing a high amount of dissolved organic matter. Keywords: AcephateMethamidophosSPEGC-MSWaterPolar pesticides Acknowledgements The authors thank the National Sciences and Engineering Research Council of Canada and the Faculté des Études Supérieures of l’Université de Moncton for their financial support.

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 categoriesnone
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 score0.047
Threshold uncertainty score0.164

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 communication0.0000.000
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 head0.010
GPT teacher head0.278
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Environmental & Analytical ChemistrySame topicPesticide Residue Analysis and SafetyFrench-language works237,207