World Workshop on Oral Medicine VII: Relative frequency of oral mucosal lesions in children, a scoping review
Bibliographic record
Abstract
OBJECTIVE: To detail a scoping review on the global and regional relative frequencies of oral mucosal disorders in the children based on both clinical studies and those reported from biopsy records. MATERIALS AND METHODS: A literature search was completed from 1 January 1990 to 31 December 2018 using PubMed and EMBASE. RESULTS: Twenty clinical studies (sample size: 85,976) and 34 studies from biopsy services (40,522 biopsies) were included. Clinically, the most frequent conditions were aphthous ulcerations (1.82%), trauma-associated lesions (1.33%) and herpes simplex virus (HSV)-associated lesions (1.33%). Overall, the most commonly biopsied lesions were mucoceles (17.12%), fibrous lesions (9.06%) and pyogenic granuloma (4.87%). By WHO geographic region, the pooled relative frequencies of the most common oral lesions were similar between regions in both clinical and biopsy studies. Across regions, geographic tongue (migratory glossitis), HSV lesions, fissured tongue and trauma-associated ulcers were the most commonly reported paediatric oral mucosal lesions in clinical studies, while mucoceles, fibrous lesions and pyogenic granuloma were the most commonly biopsied lesions. CONCLUSIONS: The scoping review suggests data from the clinical studies and biopsy records shared similarities in the most commonly observed mucosal lesions in children across regions. In addition, the majority of lesions were benign in nature.
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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 | 0.021 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.034 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".