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Record W2310447794 · doi:10.3920/cep150036

Effect of exercise on gastric health in field retrievers

2016· article· en· W2310447794 on OpenAlexaffabout
Michael S. Davis, Μ. D. Willard, Michael Day, J P McCann, Mark E. Payton, Sabrina Cummings

Bibliographic record

VenueComparative Exercise Physiology · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsStillwater (Canada)
Fundersnot available
KeywordsMedicineHistopathologyDiseaseAthletesInternal medicineEndoscopyGastroenterologyPathologyPhysical therapy

Abstract

fetched live from OpenAlex

Exercise-induced gastrointestinal disease (EIGD) has been reported in all domestic athletes. In dogs and humans, EIGD is most commonly associated with ultra-endurance racing sled dogs and marathon/triathlon competitors, respectively, suggesting that the syndrome is specifically a function of prolonged exercise. However, EIGD is also common in horses that exercise for brief periods, and more recently, EIGD has been identified in Labrador retrievers that perform off-leash explosive detection patrols. In this study, we tested the hypothesis that EIGD could be induced in retrievers performing competition-style retrieves. Gastric endoscopy and histopathological examination of gastric biopsies were performed on 10 healthy retrievers before and 24 h after a series of multi-set retrieves totalling over 5 km. Although the exercise challenge resulted in a small but statistically significant increase in gastric endoscopy severity score, it did not result in a higher prevalence of clinically-significant gastric disease or changes in gastric histopathology. We conclude that competitive retrieving is unlikely to induce clinically-significant gastric disease in healthy 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
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 head0.092
GPT teacher head0.434
Teacher spread0.342 · 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 designObservational
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
Published2016
Admission routes2
Has abstractyes

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