Assessment of Body Condition in Long-Distance Sled Dogs: Validation of the Body Condition Score and Its Association with Ultrasonographic, Plicometric, and Anthropometric Measurements
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Bibliographic record
Abstract
This study aimed to validate the 9-point body condition score (BCS) system in sled dogs by assessing its reliability and by comparing it with objective measures including real-time ultrasonography, plicometry, and anthropometry. Twenty-seven Siberian Huskies (11 females, 16 males) from three sled dog teams were assessed for BCS by three trained veterinarians and their respective mushers. Intra-observer reliability was substantial (Krippendorff’s α = 0.734), while agreement between expert raters (Kα = 0.580) and between the expert rater and mushers (Kα = 0.691) was moderate, with mushers tending to overestimate the BCS of their own dogs (median difference = −0.5). BCS showed positive correlations with body mass index (BMI) and subcutaneous fat at the chest and flank via plicometry (for all: p < 0.05). Ultrasonography showed weak correlations with BCS, likely due to the different anatomical layers evaluated and the distinctively high muscle-to-fat ratio typical of sled dogs. Both univariate and multivariate analyses revealed sex- and neutering-related differences in body composition, with males generally presenting larger skeletal dimensions and neutering influencing patterns of fat distribution. These findings support the reliability and field applicability of the BCS system when used by trained evaluators, highlighting the importance of considering sex and anatomical site when assessing body condition in athletic dogs. The 9-point BCS, combined with accessible objective tools, represents a consistent, cost-effective method for monitoring body condition in long-distance performance sled dogs.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it