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<i>Ex Vivo</i> Comparison of Bursting Strength of Ventral Median and Right Ventral Paramedian Celiotomies in Horses

2013· article· en· W1579237494 on OpenAlexaff
Stacy Anderson, José L. Bracamonte, S. Hendrick, James L. Carmalt, David G. Wilson

Bibliographic record

VenueVeterinary Surgery · 2013
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBurstingMedicineCadaverAnatomyHorseAbdomenSurgeryBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare bursting strength and failure mode between ventral median (VM) and right ventral paramedian (RVP) celiotomies closed with 1 section of USP 7 braided polydioxanone (7PD). STUDY DESIGN: Ex vivo experimental. ANIMALS: Equine cadavers (n = 12). METHODS: A 25 cm VM or RVP (positioned 5 cm lateral to the linea alba) celiotomy was created in fresh equine cadavers. A 200 L polyurethane bladder was inserted into the abdomen. Celiotomies were closed in a simple continuous pattern with 1 section of 7PD. The bladder was inflated with compressed air until construct failure. Horse signalment, body weight, celiotomy type, failure mode (suture or abdominal wall), failure location (adjacent or remote from the celiotomy), and bursting strength (mmHg) were recorded. Interactions between independent and dependent variables were assessed with statistical tests including linear regression. RESULTS: Increasing age (P = .002) and Quarter horse-type breed (P = .01) had a negative effect on bursting strength. When age and breed were controlled, RVP celiotomies had a lower bursting strength compared with VM celiotomies (P = .039). None of the celiotomies failed at the suture. CONCLUSION: VM celiotomies have a greater bursting strength than RVP celiotomies when age and breed are controlled. Celiotomy bursting strength decreases with increasing age and is lower in Quarter horse-type breeds compared with non-Quarter horse-type breeds.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.365
Teacher spread0.270 · 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.

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

Citations16
Published2013
Admission routes1
Has abstractyes

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