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Poisoning of a dog with the explosive pentaerythrityl tetranitrate

2008· article· en· W2154714995 on OpenAlexaboutno aff
Dalibor Potočnjak, Renata Barić-Rafaj, Nikša Lemo, Vesna Matijatko, István Emil Kis, Vladimir Mrljak, I. Harapin

Bibliographic record

VenueJournal of Small Animal Practice · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineExplosive materialPentaerythritol tetranitrateLabrador RetrieverSurgery

Abstract

fetched live from OpenAlex

A three-year-old male Labrador retriever was presented at the Clinic of Internal Medicine, University of Zagreb, Croatia. The owner reported that the dog was ataxic, and this was evident by its markedly unsteady, swaying gait. The dog also had difficulty rising and fell several times while trying to stand. It had come into contact with the explosive, pentaerythrityl tetranitrate, while training to detect explosives. The following clinical symptoms were observed: bradycardia, depression, mild disorientation and a broad-based stance. The dog had conscious proprioceptive deficits in the hindlimbs, but cranial nerve function was normal except for miosis. Ion scan analysis of the dog's serum after evaporation of the current phase by mass spectroscopy revealed the presence of fragments that are characteristic of pentaerythrityl tetranitrate. The aim of the present case report was to identify pentaerythrityl tetranitrate poisoning and describe the clinical signs of pentaerythrityl tetranitrate poisoning in dogs. To the authors' knowledge, there are no published scientific articles on pentaerythrityl tetranitrate poisoning in dogs.

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
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 head0.029
GPT teacher head0.283
Teacher spread0.254 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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