A longitudinal assessment of periodontal health status in 53 Labrador retrievers
Bibliographic record
Abstract
OBJECTIVES: To determine the incidence and rates of progression of gingivitis and periodontitis in Labrador retrievers. MATERIALS AND METHODS: Fifty-three dogs, aged 1·1 to 5·9 years, had their periodontal health assessed every 6 months for up to 2 years. The extent of gingivitis and periodontitis was measured around the whole gingival margin of every tooth under general anaesthesia. RESULTS: All dogs had gingivitis at the initial assessment. The majority (64·2%) of tooth aspects had very mild gingivitis. The palatal/lingual aspect of all tooth types was most likely to show bleeding when probed: 63·0% of these aspects had mild or moderate gingivitis. Over 2 years, 56·6% of dogs developed periodontitis and dogs as young as 1·9 years were affected. There was a significant positive correlation between the proportion of teeth with periodontitis and age. In total, 124 teeth (5·7%) developed periodontitis; 88 (71·0%) of these were incisors. The palatal/lingual aspect of the incisors developed the disease first (2·8% of incisor aspects). CLINICAL SIGNIFICANCE: Periodontitis developed in regions that are difficult to see in conscious dogs implying that detection and treatment of disease requires periodic sedation or anaesthesia.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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".