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Record W2738147165 · doi:10.12968/vetn.2017.8.6.338

Acute Hepatopathy and Coagulopathy in the Canine: A Nursing Care Report

2017· article· en· W2738147165 on OpenAlexaboutno aff
Andrew Rushent

Bibliographic record

VenueThe Veterinary Nurse · 2017
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoagulopathyIntensive care medicineNursing careVomitingMedical diagnosisNursingMedical emergencySurgery

Abstract

fetched live from OpenAlex

This nursing care report discusses the treatment and management of acute hepatopathy and secondary coagulopathy in the canine as well as the impact this case had on the development of the author's nursing ability. The patient, a nine-year-old Labrador Retriever, was referred for treatment after an episode of vomiting followed by collapse during a walk with their owner. On presentation the patient was tachycardic, tachypnoeic with absent peripheral pulses. After haematological and biochemical analysis of the patient's blood, the clinical team implemented a medical care plan based on two differential diagnoses; xylitol poisoning or leptospirosis. The nursing team delivered an intensive care regimen including extensive patient monitoring, environmental modification, assisted feeding and blood transfusion with strict adherence to barrier nursing protocols. Fortunately, due to the dedicated efforts of the clinical team, the patient successfully recovered and was returned to their family in good health.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.064
GPT teacher head0.395
Teacher spread0.331 · 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
Published2017
Admission routes1
Has abstractyes

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