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Record W7015749331

Ultrasonic Study of Normal Tendons and Ligaments of the American Quarter Horse

2014· article· en· W7015749331 on OpenAlexaboutno aff

Bibliographic record

VenueScholarsArchive (Brigham Young University) · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
Fundersnot available
KeywordsSuspensory ligamentCircumferenceQuarter (Canadian coin)ForelimbPurebredHorseTendonLigamentUltrasonography
DOInot available

Abstract

fetched live from OpenAlex

The palmar metacarpal aspect of 27 purebred (n=24) and appendix (n=3) American Quarter Horses were divided into sections and ultrasonically viewed to determine the circumference and cross-sectional area of the four principle tendons and ligaments in this region: superficial digital flexor tendon, deep digital flexor tendon, inferior check ligament, and suspensory ligament. This study was conducted using Brigham Young University Equitation schooling horses between May 1997 and February 1998. The structure measurements were analyzed for relationships to weight, age, sex and size of the horses (n=27). No correlation between weight, age, and sex of the horse and dimensions of any of the structures was found at any zone. No significant difference was found between measurements of the tendons and ligaments of left and right forelegs. These findings offer veterinarians a reference point to aid in diagnosis of forelimb injuries, such as tendon and ligament strains or tears. Hence, practitioners can more objectively evaluate the treatment response of an injured Quarter Horses by comparing the measurements of the injured leg to that of the normal leg.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.289
Teacher spread0.265 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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