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Components of variation of surface hoof strain with time

2001· article· en· W2169422446 on OpenAlexafffund
J. J. Thomason, W. Bignell, W. SEARS°

Bibliographic record

VenueEquine Veterinary Journal · 2001
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsHoofRepeatabilityGaitStrain gaugeTrimmingCoefficient of variationStrain (injury)MathematicsAnalysis of varianceOrthodonticsBiologyAnatomyStatisticsMedicineMaterials sciencePhysical medicine and rehabilitationComposite material

Abstract

fetched live from OpenAlex

The relative contribution of a number of random and fixed variables to variation in surface strain magnitudes on the hoof capsule was assessed for healthy feet under normal conditions. Principal strains were recorded in vivo from 5 rosette gauges glued around the circumference of the right forefeet of 4 horses on 4 occasions over a 9 month period. Recordings were made at every other trimming and reshoeing. During each session, gauges were positioned with a template for repeatability. Strains were recorded at the trot and canter (at consistent speeds), for straight motion and turns, and before and after the hoof was trimmed and reset. Up to 30 strides were recorded for each combination of these variables. ANOVAs were performed on midstance strains of 7008 strides to determine the relative contributions to strain variation of individual horse, test day, gait and direction combined as one factor, gauge position on the hoof, trimming, interstride variability and the interactions among these factors. The ANOVA model explained 87% of the variation, of which approximately 84% was due to fixed effects and 16% to random effects. Circumferential position of the gauges and several of the interactions including this term were by far the greatest contributors to strain variation. Differences among gauge positions, individuals and gait + direction are consistent with previous work. This study has added the relative effects, which are small but significant, of trimming on a regular basis and of time. The change in strain magnitudes with trimming was different for each horse, which leads to the possibility that over- and underuse may have to be quantified on an individual basis.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.111
GPT teacher head0.368
Teacher spread0.257 · 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 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

Citations10
Published2001
Admission routes2
Has abstractyes

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