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Record W2145943807 · doi:10.1002/etc.3243

A four-country ring test of nontarget effects of ivermectin residues on the function of coprophilous communities of arthropods in breaking down livestock dung

2015· article· en· W2145943807 on OpenAlexaffabout
Thomas Tixier, Wolf U. Blanckenhorn, J. Lahr, Kevin D. Floate, Adam Scheffczyk, Rolf‐Alexander Düring, Manuel Wohde, Jörg Römbke, Jean‐Pierre Lumaret

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2015
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsAgriculture and Agri-Food Canada
FundersDeutsche Bundesstiftung Umwelt
KeywordsIvermectinLivestockBiologyToxicologyEcology

Abstract

fetched live from OpenAlex

By degrading the dung of livestock that graze on pastures, coprophilous arthropods accelerate the cycling of nutrients to maintain pasture quality. Many veterinary medicinal products, such as ivermectin, are excreted unchanged in the dung of treated livestock. These residues can be insecticidal and may reduce the function (i.e., dung-degradation) of the coprophilous community. In the present study, we used a standard method to monitor the degradation of dung from cattle treated with ivermectin. The present study was performed during a 1-yr period on pastures in Canada, France, The Netherlands, and Switzerland. Large effects of residue were detected on the coprophilous community, but degradation of dung was not significantly hampered. The results emphasize that failure to detect an effect of veterinary medicinal product residues on dung-degradation does not mean that the residues do not affect the coprophilous community. Rather, insect activity is only one of many factors that affect degradation, and these other factors may mask the nontarget effect of residues. Environ Toxicol Chem 2016;35:1953-1958. © 2015 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0010.001
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 head0.020
GPT teacher head0.240
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2015
Admission routes2
Has abstractyes

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