Inter‐ and Intratester Reliability of Anthropometric Assessment of Limb Circumference in Labrador Retrievers
Bibliographic record
Abstract
OBJECTIVE: To report a standardized method of, and determine inter- and intratester reliability for, anthropometric assessment of limb circumference in dogs. STUDY DESIGN: Prospective blinded study. ANIMALS: Labrador Retrievers (n = 20). METHOD: Unsedated dogs were manually restrained in lateral recumbency and triplicate measurements of limb circumference at the level of the proximal antebrachium, mid brachium, proximal crus, and mid-thigh were made using the Gulick II tape measure in the morning and afternoon of the same day. Observers were blinded to measurements made during each occasion and those made by co-observers. Estimates of inter- and intratester reliability were made for first and mean measurements using intra-class correlation coefficients (ICC). RESULTS: Measurements of the proximal antebrachium were made with moderate to fair intratester reliability by all observers with ICC's ranging from 0.68-0.78 (1st measurement) and 0.67-0.78 (mean measurement), and moderate to fair intertester reliability with ICC's of 0.66-0.68 (1st measurement) and 0.70-0.72 (mean measurement). Measurements of the brachium, crus, and thigh typically had poor inter- and intratester reliability, ICC < 0.5. CONCLUSION: Using the described method of muscle measurement in Labrador Retrievers only measurement of the proximal antebrachium was reliable; a single (1st) measurement was as reliable as using the mean of triplicate measurements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".