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<i>Ex Vivo</i> Evaluation of Carpal Flexion After Partial Carpal Arthrodesis in Horses

2014· article· en· W1918703827 on OpenAlexaff
Patty J. Tulloch, James D. Johnston, Spencer Μ. Barber, Candace L. Gellert, Hayley M. Lang, Luca Panizzi

Bibliographic record

VenueVeterinary Surgery · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsArthrodesisMedicineCarpal JointHorseOsteoarthritisOrthodonticsSurgeryWrist

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine degrees of flexion after arthrodesis of the antebrachiocarpal (ABC) joint, middle carpal (MC), and carpometacarpal (CMC) joints combined (MC/CMC), and carpometacarpal (CMC) joint alone. STUDY DESIGN: Ex vivo study. ANIMALS: Forelimbs (n = 9) from 2- to 10-year-old Quarter Horses (5), Thoroughbred (2), and American Paint Horse (2). METHODS: Using 2 locking compression plates, 3 partial carpal arthrodesis techniques were performed. Cables and deadweights were connected to limbs and each angle of flexion determined 3 times using a protractor and then averaged. Control measurements were obtained before and after arthrodesis, the techniques randomized with Latin square design. Descriptive data were analyzed with Levene's test, Q-Q plots, ANOVA, and Bonferroni test. RESULTS: Mean ± SD carpal flexion results were: controls 150° ± 8°, CMC arthrodesis 149° ± 9°, MC/CMC arthrodesis 43° ± 7.6°, and ABC arthrodesis 25° ± 6.3°. There was no significant reduction in flexion after a CMC arthrodesis compared with controls (P = .21), but there was after ABC (P < .001) and MC/CMC arthrodesis (P < .001), with the ABC arthrodesis significantly reduced compared with an MC/CMC arthrodesis (P < .001). CONCLUSIONS: Whereas CMC arthrodesis does not affect carpal flexion, CMC/MC and ABC arthrodesis markedly reduce the degree of carpal flexion.

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)0.006
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.176
GPT teacher head0.396
Teacher spread0.220 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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