Evaluation of serum cobalamin concentrations in dogs of 164 dog breeds (2006–2010)
Bibliographic record
Abstract
Altered serum cobalamin concentrations have been observed in dogs with gastrointestinal disorders such as exocrine pancreatic insufficiency (EPI) or gastrointestinal inflammation. The aims of the current study were 1) to identify breeds with a higher proportion of dogs with a decreased serum cobalamin concentration, 2) to determine whether dogs with such decreased concentrations tend to have serum canine trypsin-like immunoreactivity (cTLI) concentrations diagnostic for EPI, and 3) to compare the number of submissions for serum cobalamin analysis by breed to the American Kennel Club (AKC) breed ranking list of 2009. In this retrospective study, results of 28,675 cobalamin tests were reviewed. Akitas, Chinese Shar-Peis, German Shepherd Dogs, Greyhounds, and Labrador Retrievers had increased proportions of serum cobalamin concentrations below the lower limit of the reference interval (<251 ng/l; all P < 0.0001). Akitas, Chinese Shar-Peis, German Shepherd Dogs, and Border Collies had increased proportions of serum cobalamin concentrations below the detection limit of the assay (<150 ng/l; all P < 0.0001). Akitas, Border Collies, and German Shepherd Dogs with serum cobalamin concentrations <150 ng/l were more likely to have a serum cTLI concentration considered diagnostic for EPI (≤2.5 µg/l; all P ≤ 0.001). The breed with the highest proportion of samples submitted for serum cobalamin analysis in comparison with the AKC ranking list was the Greyhound (odds ratio: 84.6; P < 0.0001). In Akitas and Border Collies, further investigations are warranted to clarify if a potentially breed-specific gastrointestinal disorder is responsible for the increased frequency of decreased serum cobalamin and cTLI concentrations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 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".