Practical application of a method for assessing the progression of gingival recessions in orthodontically treated patients--a pilot study.
Bibliographic record
Abstract
AIMS: The objective of the present study was to discuss the practical application of a new method for measuring bone width in the anterior section of the mandible to assess the progression of gingival recessions after orthodontic treatment based on a description of case studies. METHODS: Three cases with skeletal classes I, II and III aged 20-29 were presented. We assessed the risk of gingival recessions around lower incisors by analysing cephalograms before and after orthodontic treatment. The following values were analysed: the angle of buccal bone thickness in the anterior section of the mandible (API-CEJ2-B), the height of bone dehiscence (CEJ2-Id) and the width of the mentalis (B-D). Recession height (RD) and width (RW) were clinically measured using calibrated 1mm periodontometer. RESULTS: The mean baseline angle of API-CEJ2-B[°] was 22.23° before and no lower than 16° after treatment. In all patients CEJ2-Id was 0.56 mm before and greater than 1.4 mm following treatment. This was reflected clinically in the absence of new gingival recessions or the progression of an already existing recession in the area of the lower incisors in the first two cases. In the third case, height of recessions was increased to 1.25 mm average value. The mean baseline width for B-D was 13.46 mm; in all cases it increased up to 14.5 mm after treatment, most significantly in the case of a female patient with skeletal class II. CONCLUSIONS: An analysis of cephalometric images, including basic cranio- and gnathometric measurements together with a careful assessment of bone, mucosal and dental parameters of the alveolar ridge, can be a useful instrument to determine the risk of gingival recessions and to choose the right orthodontic treatment option, ensuring the highest possible aesthetic-functional treatment outcome.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".