MétaCan
Menu
Back to cohort
Record W2322246106 · doi:10.1584/jpestics.w12-24

GABA A receptor antagonistic insecticide fipronil: Overview of toxicological studies

2012· article· en· W2322246106 on OpenAlexaff
Atsushi Suzuki, Ayumi Aoki, Masami Fujiwara, Osamu Koto, Masako Akiyama, Atsushi Suzuki

Bibliographic record

VenueJournal of Pesticide Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsFipronilToxicityPharmacologyBiologyGABAergicToxicologyReceptorInternal medicinePesticideMedicineBiochemistry

Abstract

fetched live from OpenAlex

Fipronil is a phenylpyrazole-class insecticide used for rice protection, and its pharmacological activity is an interruption of the GABA A receptor. Since fipronil suppresses GABAergic neurons, central nervous system (CNS) toxicity is well observed. However, fipronil has no influence on neurogenesis. Fipronil promoted hepatocyte vacuolization and thyroid oncogenesis only in rats. It had no genotoxic activity, and thyroid oncogenesis was promoted by accelerated thyroxin clearance under the genetic lack of thyroxine-binding globulin (TBG), suggesting an apparent rat-specific mechanism. Therefore, in relation to human health concerns, the most important toxicity of fipronil would be CNS toxicity, which was commonly observed in most of the toxicological studies with various species. Most of the NOAELs were established by CNS toxicity, and a minimum value was contributed for the ADI setting. Thus, the safety and human risk assessments are well ensured by the ADI.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.185
GPT teacher head0.395
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pesticide ScienceSame topicInsect and Pesticide ResearchFrench-language works237,207