200 A Scoring System for Equine Dental Health
Bibliographic record
Abstract
Abstract Scoring systems have been implemented in veterinary practice to indicate the severity of pathologies, such as lameness and gastric ulceration. The need for a scoring system of equine dentition in relation to digestive health has been identified. A scoring system would allow veterinarians, owners, and researchers to more accurately assess dental health and the resulting impact it may have on chewing ability. A proposed system, the Equine Dental Scoring System (EDSS), was developed via collaboration of a team of veterinarians and equine nutritionists familiar with equine dental abnormalities. The EDSS was designed to assign higher scores corresponding to increasing severity of dental abnormalities that would impede proper chewing. The proposed scoring system ranges from 0 to 5 as follows: 0) no sharp enamel points, soft tissue damage, or malocclusion, (1) sharp enamel points, but no soft tissue damage or malocclusion, (2) sharp enamel points and soft tissue damage, but no malocclusion, (3) mild malocclusion with all aligned teeth meeting level (ex. ramps, hooks), (4) moderate malocclusion with all teeth meeting but not level (ex. wave, smile, diagonal, frown), (5) major malocclusion with one or more teeth not meeting or inhibited temporomandibular joint movement (ex. step, shear, retained cap), and/or infection, and/or pain while chewing. The EDSS was validated by assessing agreement via the Cohen’s kappa statistic between four trained professionals scoring ten images of horse dentition. Both the weighted (к = 0.62) and unweighted (к = 0.73) kappa statistics indicated substantial agreement between scorers, signifying reliable repeatability of the EDSS. Presenting dental health in the form of a score would indicate severity of dental pathologies and allow for quantitative and statistical evaluation of dental health in nutrition research and veterinary medicine.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".