A Survey of Equine Oral Pathology
Bibliographic record
Abstract
Dental abnormalities in horses can lead to weight-loss, poor performance, pain, behavioral abnormalities, and illness. Despite this impact, the occurrence and type of dental disease in horse populations is infrequently reported in veterinary medicine. The purpose of this cross-sectional survey of horses presented for slaughter at a processing plant in Western Canada was to measure the prevalence of equine oral abnormalities, examine associations between the most common abnormalities, and consider the relationship between the age of horse and types of abnormalities observed. The horses used in this research consisted of a variety of ages, breeds, body conditions, and origins. Horses ranged in age from 18-months to 30-years (median = 11-years). The most common oral pathologies included sharp edges, buccal abrasions, calculus, lingual ulcers, gingival recession, periodontal pockets, ramps, and waves. Several types of pathology were strongly associated with other dental disorders. The prevalence of periodontal pockets, gingival recession, and waves was highest in older horses.
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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 | 0.000 | 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 | 0.001 | 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) | 0.001 | 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".