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Record W2963670130 · doi:10.2460/ajvr.80.8.736

Investigation of white line separation under load in bovine claws with and without toe-tip necrosis

2019· article· en· W2963670130 on OpenAlexaff
James D. Johnston, Dustin James Robert Eichhorn, Saija Kontulainen, Scott D. Noble, Murray Jelinski

Bibliographic record

VenueAmerican Journal of Veterinary Research · 2019
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsClawHoofCadaveric spasmAnatomyMaterials scienceBiomedical engineeringBiologyMedicineStructural engineeringEngineering

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the degree of white line separation created by increasing physiologic loads between bovine claws with and without toe-tip necrosis (TTN). SAMPLE: Cadaveric bovine hind limbs with (n = 10) and without (10) TTN. PROCEDURES: Hind limbs in which 1 or both claws had evidence of apical white line separation were considered to have TTN. Hind limbs in which neither claw had evidence of white line separation were considered controls. Each hind limb was mounted in a materials testing system with the bottom surface of the hoof angled at approximately 5° to the horizontal plane such that the apex of the claws made initial contact with the clear testing surface to simulate physiologic loading conditions. A digital camera mounted underneath the testing surface was used to obtain images of the bottom of the hoof during the application of each of 3 increasing static loads (1, 2, and 3 kN). The images were analyzed with commercial image-processing software to quantify white line separation area. RESULTS: White line separation area was significantly greater for claws with TTN than for control claws and increased as the applied load increased. White line separation was almost nonexistent in control claws and was not affected by increasing load. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that mechanical loading exacerbated TTN, but compressive loading alone, even at excessive levels, did not initiate the condition. Interventions (eg, hoof blocks) that decrease loading of affected claws may be beneficial for the treatment of TTN at its earliest stages.

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)0.002
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 score0.396
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.146
GPT teacher head0.423
Teacher spread0.277 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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