Oral Health Scales: Design of an Oral Health Scale of Infectious Potential
Bibliographic record
Abstract
OBJECTIVES: In this paper we propose a new Global Oral Health Scale that will allow the infectious potential of the oral cavity, clinically manifest as local and focal infections, to be condensed into a single parameter. STUDY DESIGN: Based on a number of oral health scales previously designed by our group, we designed a final version that incorporates dental and periodontal variables (some of them evaluated using corroborated objective indices) that reflect the presence of caries and periodontal disease. RESULTS: The application of the proposed oral health scale requires the examination of 6 sites per tooth (mesio-buccal, medio-buccal, disto-buccal, disto-lingual, medio-lingual and mesio-lingual). The following variables are analysed: number of tooth surfaces with supragingival plaque, determined using the O'Leary index; number of teeth with caries and the severity of the caries; number of tooth surfaces with gingival inflammation, determined using the Ainamo and Bay index; and number of tooth surfaces with pockets ≥ 4 mm and severity of the pockets. These variables are then grouped into 2 categories, dental and periodontal. The final grades of dental and periodontal health correspond to the grades assigned to a least 2 of the 3 variables analysed in each of these categories. The category (dental or periodontal) with the highest grade is the one that determines the grade of the Global Oral Health Scale. CONCLUSION: This scale could be particularly useful for the epidemiological studies comparing different populations and for analysis of the influence of distinct degrees of oral health on the development of certain systemic diseases.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".