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Record W4396534375 · doi:10.31080/asvs.2024.06.0863

Management of Organophosphate Compound (Dichlorvos) Poisoning in a Labrador Retriever Dog: A Case Study

2024· article· en· W4396534375 on OpenAlexaboutno aff
Kajal Bhardwaj, Raman Yadav

Bibliographic record

VenueActa Scientific Veterinary Sciences · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLabrador RetrieverDichlorvosOrganophosphateOrganophosphate poisoningMedicineBiologySurgeryPesticideEcology

Abstract

fetched live from OpenAlex

Organophosphate (OP) poisoning is a prevalent type of toxicity in animals, primarily due to its extensive application as an insecticide and anthelmintic, coupled with its easy accessibility.Intoxication occurs when OP agents are absorbed through the gastrointestinal tract, skin and respiratory tract.The clinical manifestations vary based on the quantity of poison ingested, its concentration and the route of exposure.This study deals with successful management of OP poisoning case in male Labrador dog of age around 18 months age, brought to ICAR-IVRI, RVP-TVCC, Izzatnagar with history of accidently exposure to dichlorvos (Organophosphate) while bathing with symptoms of excessive salivation, tachypnea, unconsciousness, hypethermia and miosis.Case was successfully managed with immediate treatment of 2-PAM (specific antidote to OP poisoning) and atropine sulphate after proper washing of body with water along with symptomatic treatment that continued further for 7 days.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.295
Teacher spread0.261 · 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 designCase report
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

Citations0
Published2024
Admission routes1
Has abstractyes

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