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Thoracic Limb Alignment in Healthy Labrador Retrievers: Evaluation of Standing Versus Recumbent Frontal Plane Radiography

2014· article· en· W1514125926 on OpenAlexaboutno aff
Zachary J. Goodrich, Bo Norby, Bunita Eichelberger, Wade O. Friedeck, Hollye N. Callis, Don A. Hulse, Sharon C. Kerwin, D. B. Fox, W. Brian Saunders

Bibliographic record

VenueVeterinary Surgery · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiographyElbowBody weightLower limbBody positionAnatomyOrthodonticsNuclear medicinePhysical medicine and rehabilitationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To report thoracic limb alignment values in healthy dogs; to determine if limb alignment values are significantly different when obtained from standing versus recumbent radiographic projections. STUDY DESIGN: Prospective cross-sectional study. ANIMALS: Labrador Retrievers (n = 45) >15 months of age. METHODS: Standing and recumbent radiographs were obtained and limb montages were randomized before analysis by a single investigator blinded to dog, limb, and limb position. Twelve limb alignment values were determined using the CORA methodology. Measurements were performed in triplicate and intra-observer variability was evaluated by intra-class correlation coefficient (ICC). Limb alignment values were reported as mean ± SD and 95% confidence intervals. Linear mixed models were used to determine if significant associations existed between limb alignment values and limb, limb position, gender, age, weight, and body condition score. RESULTS: There were significant differences in standing and recumbent limb alignment values for all values except elbow mechanical axis deviation (eMAD). Limb, gender, age, body weight, and body condition score had no effect. ICC values ranged from 0.522 to 0.758, indicating moderate to substantial agreement for repeated measurements by a single investigator. CONCLUSIONS: Limb alignment values are significantly different when determined from standing versus recumbent radiographs in healthy Labrador Retrievers.

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)0.004
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0000.000

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 head0.177
GPT teacher head0.378
Teacher spread0.202 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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