Prevalence of mandibular asymmetries in growing patients
Bibliographic record
Abstract
The aim of the present study was to determine the prevalence of mandibular asymmetries during the mixed dentition in growing children. For this purpose, a retrospective study was designed where various measurements were performed on the right and left sides of the mandible of panoramic radiographs of 327 children (males: 169; females: 158), 8-12 years old. Four linear measurements, mandibular ramus height, ramus width, corpus height, and corpus length, and two angles, mandibular gonial (Go) and mandibular condyle (Co), and the developmental stage of the permanent lower second molar were analysed. All measurements were adjusted for the magnification factor. The final data were then processed for the asymmetry index (AI) to determine the severity of the asymmetries and statistically analysed by Wilcoxon paired tests at the 95 per cent level of confidence. A moderate-to-severe mandibular asymmetry for the linear dimensions when both sides of the mandible were contrasted was found in more than a half of the sample. There was also a high prevalence of moderate and severe asymmetries when comparing Go and Co angles on both sides of the mandible. No differences were observed in the developmental stage of the lower permanent second molar between either side. There was a high prevalence of both dimensional and angular mandibular asymmetries in the studied population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".