[no title]
Bibliographic record
Abstract
Periodontal disease is one of the most common conditions affecting dogs worldwide and is reported to be particularly prevalent in racing greyhounds. A range of potential risk factors have been hypothesised. Previous research has suggested that regular tooth brushing can reduce both calculus and gingivitis, but the frequency required is unclear. Here, we report a controlled blinded in situ trial, in which kennel staff brushed 160 racing greyhounds’ teeth (living at six kennel establishments), either weekly, daily or never over a two-month period. All of the visible teeth were scored for calculus and gingivitis, using previously validated scales. We calculated average scores for each of the three teeth groups and overall whole mouth scores, averaging the teeth groups. Changes were compared to the baseline. After two months, the total calculus scores (controlling for baseline) were significantly different in the three treatment groups, (F(2,129) = 10.76, p < 0.001) with both weekly and daily brushing resulting in significant reductions. Gingivitis was also significantly different between groups (F(2,128) = 4.57, p = 0.012), but in this case, only daily brushing resulted in a significant reduction. Although the dogs in different kennels varied significantly in their levels of both calculus (F(5,129) = 8.64, p < 0.001) and gingivitis (F(5,128) = 3.51 p = 0.005), the intervention was similarly effective in all of the establishments. The teeth groups varied, and the incisors were not significantly affected by the treatment. Since the trainers implementing the routine, reported a minimal time commitment and positive experiences, we suggest that daily brushing is recommended for racing greyhounds, and that any instructions or demonstrations should include attention to all teeth groups including the incisors. Similar trials need to be conducted with retired greyhounds since these have been shown to present particularly high levels of periodontal disease.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".