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Record W2068763195 · doi:10.1160/vcot-06-09-0071

Rotating dome trochleoplasty: An experimental technique for correction of patellar luxation using a feline model

2007· article· en· W2068763195 on OpenAlexaff
Kathleen Linn, M Gillick

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2007
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsSaskatchewan PolytechnicUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineDome (geology)PatellaAnatomyCadaverArticular surfaceOrthodonticsGeologyGeomorphology

Abstract

fetched live from OpenAlex

The purpose of this study was to compare a trochlear block recession to a rotating dome trochleoplasty, a novel technique for the correction of patellar luxation in small animals. Twenty-eight limbs were used from 14 feline cadavers. With the stifles in flexion and extension, computed tomography was utilized to compare width and depth of the trochlea, medial trochlear ridge height, trochlear articular surface area preserved, patellar contact articular surface area, patellar area covered by the trochlear ridges and patellar tilt angle. The results of this study demonstrated that a rotating dome trochleoplasty is superior to a trochlear block recession with regard to medial trochlear height, trochlear width, trochlear depth and trochlear surface area preservation. The results of this study support further biomechanical evaluation of this technique which eventually may lead to clinical trials.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.193
GPT teacher head0.398
Teacher spread0.205 · 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 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

Citations7
Published2007
Admission routes1
Has abstractyes

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