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Record W1606087062

The use of veterinary cuttable plates for carpal and tarsal arthrodesis in small dogs and cats.

2007· article· en· W1606087062 on OpenAlexaff
Marie-Claude Théoret, Noël Moens

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineArthrodesisTarsal JointCATSPressure soresSurgeryLamenessWeight-bearingCarpal JointVeterinary medicineWrist
DOInot available

Abstract

fetched live from OpenAlex

The objective of the study was to evaluate, retrospectively, carpal and tarsal arthrodesis in small dogs and cats by using veterinary cuttable plates in 6 animals and comparing those with arthrodesis stabilized with other implants in 9 animals. Veterinary cuttable plates were used for 1 pancarpal, 2 partial tarsal, and 3 pantarsal arthrodeses. Other implants were used to stabilize 1 pancarpal, 6 partial tarsal, and 2 pantarsal arthrodeses. In the veterinary cuttable plates group, complications included 2 cases with pressure sores and 1 case with screw loosening. One animal was lost to follow-up and 4 of the remaining 5 were always weight-bearing. In the other group, there were 2 cases with pressure sores, 1 case with dermatitis, and 2 cases with pin migration. Six out of 9 animals were always weight-bearing. The use of veterinary cuttable plates appears to be a suitable option with a good clinical outcome.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0010.000
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 head0.196
GPT teacher head0.299
Teacher spread0.103 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

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