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Record W4250027385 · doi:10.5897/jvmah2014.0298

Comparison of range of motion in Labrador Retrievers and Border Collies

2015· article· en· W4250027385 on OpenAlexaboutno aff
L Hady Laura, T Fosgate Geoffrey, Michael Weh J

Bibliographic record

VenueJournal of Veterinary Medicine and Animal Health · 2015
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsBreedRange of motionCircumferenceRange (aeronautics)AnatomyVeterinary medicineBiologyMedicineGeographyAnimal scienceSurgeryMaterials scienceMathematicsGeometry

Abstract

fetched live from OpenAlex

The objective of this paper was to compare the range of motion in Border Collies to that of Labrador Retrievers. Humeral circumference, thigh circumference and differences between sex and age were also compared. Twenty three (23) healthy Border Collies and 18 healthy Labrador Retrievers were used. A single investigator measured range of motion of the carpus, elbow, shoulder, hip, stifle and tarsus as well as humeral and thigh circumference under field conditions in 23 Border Collies and 18 Labrador Retrievers. Border Collies had a significantly greater range of motion (P<O.001) in all joints than Labrador Retrievers. Sex was a significant predictor of range of motion (P=0.010), but age was not (P=0.400). Range of motion significantly varied by joint (P<0.001) and the effect was different within Border Collies versus Labrador Retrievers (P=0.008). Range of motion did not vary between left and right sides (P=0.365). Considerations of range of motion were made in deciding pathology and progress based on type and breed of dog (sporting, herding, protection). Comparisons were made based on breed and from left side to right side.   Key words: Range of motion, goniometry, flexion, extension, and abduction.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.429

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 head0.267
GPT teacher head0.481
Teacher spread0.214 · 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 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

Citations17
Published2015
Admission routes1
Has abstractyes

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