MétaCan
Menu
Back to cohort
Record W2949750734 · doi:10.1002/etc.4511

Assessment of Sublethal Effects of Neonicotinoid Insecticides on the Life-History Traits of 2 Frog Species

2019· article· en· W2949750734 on OpenAlexafffund
Stacey A. Robinson, Sarah D. Richardson, Rebecca L. Dalton, France Maisonneuve, Adrienne J. Bartlett, Shane R. de Solla, Vance L. Trudeau, Nigel Waltho

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of OttawaCarleton UniversityEnvironment and Climate Change Canada
FundersMinistère de l’Environnement, de la Protection de la nature et des ParcsEnvironment and Climate Change CanadaUniversity of Ottawa
KeywordsClothianidinNeonicotinoidLithobatesLeopard frogThiamethoxamBiologyMetamorphosisAmphibianLarvaImidaclopridPesticideEcotoxicologyEcologyZoologyToxicology

Abstract

fetched live from OpenAlex

Neonicotinoid insecticides are used extensively in agriculture and, as a consequence, are now detectable in nearby aquatic environments. Few studies have evaluated the effects of neonicotinoids on amphibians in these aquatic environments. In the present study, we examined the effects of 2 commercial formulations of neonicotinoids (active ingredients clothianidin and thiamethoxam) on survival and life-history traits of wood frogs (Lithobates sylvaticus) and northern leopard frogs (Lithobates pipiens). We used artificial pond mesocosms to assess the effects of these neonicotinoids, at nominal concentrations of 2.5 and 250 µg/L, on amphibian larval development through metamorphosis. We found no differences between controls and neonicotinoid exposure for any of the endpoints assessed for either wood frogs or leopard frogs. The present study suggests that concentrations meeting or exceeding observed levels of clothianidin and thiamethoxam in surface waters will not directly affect metamorphosis in 2 amphibians. Environ Toxicol Chem 2019;38:1967-1977. © 2019 SETAC.

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 categoriesInsufficient payload (model declined to judge)
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 score0.449
Threshold uncertainty score0.996

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)0.0050.000

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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 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

Citations28
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental Toxicology and ChemistrySame topicInsect and Pesticide ResearchFrench-language works237,207