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Record W2281196915 · doi:10.1021/acs.jafc.5b01347

Determination of Neonicotinoid Insecticides and Strobilurin Fungicides in Particle Phase Atmospheric Samples by Liquid Chromatography–Tandem Mass Spectrometry

2015· article· en· W2281196915 on OpenAlexafffundabout
Renata Raina‐Fulton

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeonicotinoidStrobilurinChromatographyChemistryMass spectrometryTandem mass spectrometryFungicideEnvironmental chemistryPesticideAzoxystrobinImidaclopridAgronomyBiology

Abstract

fetched live from OpenAlex

A liquid chromatography-tandem mass spectrometry method has been developed for the determination of neonicotinoids and strobilurin fungicides in the particle phase fraction of atmosphere samples. Filter samples were extracted with pressurized solvent extraction, followed by a cleanup step with solid phase extraction. Method detection limits for the seven neonicotinoid insecticides and six strobilurin fungicides were in the range of 1.0-4.0 pg/m(3). Samples were collected from June to September 2013 at two locations (Osoyoos and Oliver) in the southern Okanagan Valley Agricultural Region of British Columbia, where these insecticides and fungicides are recommended for use on tree fruit crops (apples, pears, cherries, peaches, apricots) and vineyards. This work represents the first detection of acetamiprid, imidacloprid, clothianidin, kresoxim-methyl, pyraclostrobin, and trifloxystrobin in particle phase atmospheric samples collected in the Okanagan Valley in Canada. The highest particle phase atmospheric concentrations were observed for imidacloprid, pyraclostrobin, and trifloxystrobin at 360.0, 655.6, and 1908.2 pg/m(3), respectively.

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 score0.130
Threshold uncertainty score0.209

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 head0.023
GPT teacher head0.246
Teacher spread0.223 · 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

Citations44
Published2015
Admission routes3
Has abstractyes

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