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Record W2475974775 · doi:10.1002/rcm.7581

Nitenpyram degradation in finished drinking water

2016· article· en· W2475974775 on OpenAlexaff
Matthew Noestheden, Simon C. Roberts, Chunyan Hao

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsMinistry of the Environment, Conservation and ParksFlex (Canada)Sciex (Canada)Onex (Canada)
Fundersnot available
KeywordsNeonicotinoidChemistryImidaclopridPesticideEnvironmental chemistryToxicologyEcology

Abstract

fetched live from OpenAlex

RATIONALE: Neonicotinoid pesticides and their metabolites have been indicated as contributing factors in the decline of honey bee colonies. A thorough understanding of neonicotinoid toxicity requires knowledge of their metabolites and environmental breakdown products. This work investigated the rapid degradation of the neonicotinoid nitenpyram in finished drinking water. METHODS: Nitenpyram reaction products were characterized using liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/QTOFMS). A software algorithm that compared degraded and control samples was utilized to facilitate efficient data reduction. Fragmentation pathways for six reaction products and nitenpyram were proposed using predictive software and manual product ion analysis. RESULTS: This study showed that nitenpyram degradation in unpreserved finished drinking water was likely the result of oxidation, hydrolysis and reaction with Cl2 . Structures for six nitenpyram reaction products were proposed that suggest the C9/C11 olefin as the key reactive site. CONCLUSIONS: Similarities between the identified nitenpyram reaction products and imidacloprid metabolites highlight the importance of this study, as the toxicity of neonicotinoids to pollinators has been linked to their metabolites. Based on the proposed reaction mechanisms, the identified nitenpyram reaction products in finished drinking water could also be present in the environment and water treatment facilities. As such, identifying these degradation products will aid in evaluating the environmental impact of neonicotinoid pesticides. Copyright © 2016 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.287
Teacher spread0.239 · 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

Citations29
Published2016
Admission routes1
Has abstractyes

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