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Record W4406332864 · doi:10.1111/vsu.14210

Evaluation of a patient‐specific <scp>3D</scp> ‐printed guide for ventral slot surgery in dogs: An ex vivo study

2025· article· en· W4406332864 on OpenAlexaff
Meagan Walker, Adam T. Ogilvie, Grant McSorley, William Montelpare, Katie Hoddinott

Bibliographic record

VenueVeterinary Surgery · 2025
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMedicineCadaver3d printedEx vivo3d printerSignificant differenceComputed tomographyAnatomySurgeryBiomedical engineeringIn vivo

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the accuracy of ventral slot creation in canine cadavers with a three-dimensional (3D)-printed drill guide compared to the freehand technique. STUDY DESIGN: Ex vivo study. SAMPLE POPULATION: Eight canine cadavers (23.4-39.8 kg). METHODS: Computed tomography (CT) data was used to create patient-specific 3D-printed surgical guides for ventral slot creation. Intervertebral sites were randomized to undergo either a guided (n = 12) or freehand (n = 12) ventral slot by a novice surgery resident. Postoperative CT images were used to compare ventral slot dimensions, shape, and position. RESULTS: Free-hand ventral slots were significantly shorter than the intended dimensions (p < .01). Dimensions of the guide-assisted ventral slots were not statistically different from the planned dimensions (p = .88, p = .72). Use of the guides resulted in improved accuracy for ventral slot positioning relative to midline and slot shape (difference in coefficient of variations, 32%, and 40%, respectively). CONCLUSION: Ventral slot dimensions were more accurate when created with the patient-specific 3D-printed guide compared to the freehand technique. CLINICAL SIGNIFICANCE: Use of a 3D-printed patient specific surgical guide improves accuracy of ventral slot creation in canine cadavers and improves surgical precision when used by a single novice surgical resident. The results of this study support evaluation of the guides in small breed cadavers and live patients.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
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)0.0000.000

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 head0.141
GPT teacher head0.371
Teacher spread0.230 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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