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Record W2800055937 · doi:10.1007/s11356-018-2093-0

Neonicotinoid detection in wild turkeys (Meleagris gallopavo silvestris) in Ontario, Canada

2018· article· en· W2800055937 on OpenAlexafffundabout
Amanda M. MacDonald, Claire M. Jardine, Philippe J. Thomas, Nicole M. Nemeth

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Guelph
FundersOntario Ministry of Food and AgricultureOntario Federation of Anglers and Hunters
KeywordsClothianidinNeonicotinoidThiamethoxamWildlifePesticideBiologyEcotoxicologyImidaclopridToxicologyEcology

Abstract

fetched live from OpenAlex

The use of neonicotinoid insecticides in agriculture is now recognized for the health risks it poses to non-target wildlife, with associated honey bee mortality especially concerning. Research directed toward the presence and effects of these pesticides on terrestrial vertebrates that consume neonicotinoid-coated seeds, such as wild turkeys (Meleagris gallopavo silvestris), is lacking. This study used liquid chromatography attached to a tandem mass spectrometer to assess the liver from 40 wild turkeys for neonicotinoid and other pesticide residues and compared detected levels of these contaminants across the southern Ontario, Canada. Nine (22.5%) wild turkeys had detectible levels of neonicotinoid residues-clothianidin in eight, and thiamethoxam in three. Two (5.0%) of these turkeys had detectable levels of both clothianidin and thiamethoxam. Fuberidazole was detected in two (5.0%) wild turkeys. The highest level of thiamethoxam detected was 0.16 ppm, while clothianidin was detected at 0.12 ppm, and fuberidazole at 0.0094 ppm. Knowledge of exposure in free-ranging wildlife is critical for better understanding the effects of neonicotinoids on wildlife health; thus, these data help establish baseline data for southern Ontario wild turkeys and provide context for reference values in future analyses.

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)0.002
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 score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.252
Teacher spread0.227 · 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

Citations54
Published2018
Admission routes3
Has abstractyes

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