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Record W2109954060 · doi:10.7205/milmed-d-10-00401

Emergency Canine Surgery in a Deployed Forward Surgical Team: A Case Report

2011· article· en· W2109954060 on OpenAlexaboutno aff
Alan L. Beitler, Joseph P. Jeanette, Andrew L. McGraw, Jennifer R. Butera, Christopher A. VanFosson, Jason M. Seery

Bibliographic record

VenueMilitary Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGastropexyLethargyLaparotomyGeneral surgerySurgeryLabrador RetrieverMedical emergencyStomach

Abstract

fetched live from OpenAlex

INTRODUCTION: Forward surgical teams (FSTs) perform a variety of non-doctrinal functions. During their deployment to Afghanistan, the 541st FST (Airborne) performed emergency surgery on a German shepherd military working dog (MWD). METHODS: Retrospective examination of a case of veterinary surgery in a deployed FST. RESULTS: A 5 1/2-year-old German shepherd MWD presented with extreme lethargy, tachycardia, excessive drooling, and a firm, distended abdomen. These conditions resulted from gastric dilatation with volvulus. Since evacuation to a veterinarian was untenable, emergency laparotomy was performed in the FST. The gastric dilatation with volvulus was treated by detorsion and gastropexy, and the canine patient fully recovered. CONCLUSION: Canine surgery can be safely performed in an FST. Based on the number of MWDs deployed throughout the theater, FSTs may be called upon to care for them in the absence of available veterinary care.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.114
GPT teacher head0.374
Teacher spread0.260 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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