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Record W2067452647 · doi:10.3920/cep14002

Effect of simulated deployment patrols on gastric mucosa of explosive detection dogs

2014· article· en· W2067452647 on OpenAlexaboutno aff
Michael S. Davis, Μ. D. Willard, David Bowers, Mark E. Payton

Bibliographic record

VenueComparative Exercise Physiology · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiseaseExplosive materialPhysical therapyInternal medicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Exercise-induced gastric disease is well-recognised in dogs performing ultra-endurance racing, but has not been described in dogs performing non-competitive athletic activities. Explosive detection dogs often perform prolonged periods of exercise and are reported to have chronic inappetance and weight-loss consistent with gastric disease. Seven privately-owned Labrador Retrievers trained for off-leash explosive detection activities were used to test the hypothesis that explosive detection dogs develop exercise-induced gastric disease while performing routine duties. Gastroscopy was performed on dogs before and after a 5-day exercise challenge designed to simulate routine military deployment activities. Five days of sustained submaximal exercise resulted in substantial gastric disease. These results demonstrate that dogs performing prolonged submaximal exercise consistent with off-leash explosive detection patrols are susceptible to exercise-induced gastric disease. Exercise-induced gastric disease may explain the anecdotal reports of poor thrift in these types of dogs during military deployment, and prophylactic acid suppression therapy should be considered in dogs participating in these activities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.075
GPT teacher head0.398
Teacher spread0.324 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2014
Admission routes1
Has abstractyes

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