Prevalence and measurement of anterior loop of the mandibular canal using CBCT: A cross sectional study
Bibliographic record
Abstract
BACKGROUND: Anterior loop of the mental nerve is a very important anatomic landmark in implant placement and anterior mandibular osteotomies. PURPOSE: Two-dimensional imaging techniques are not competent enough to locate and measure the mental nerve loop in majority of the cases. Any injury to this loop results in pain/paresthesia/numbness in the region supplied by the mental nerve. The aim of this study is to analyze the prevalence and measure the length of the loop using cone beam computerized tomography (CBCT) and calculate the average length and prevalence so that a safe margin can be given while placing the implants or the osteotomy cuts in the premolar region. MATERIALS AND METHODS: A cross-sectional study was done using CBCT images of 85 patients taken for impaction surgery. The length of the loop was measured in mm using standardized lines drawn along specific anatomic landmarks. RESULTS: In our study 11.76% of patients had anterior loop in their mental nerve. Mean length of the mental nerve loop was calculated and found to be 2.79 mm. CONCLUSION: A margin of 4 mm anterior to the mental foramen should be safe to avoid any damage to the mental nerve loop bundle in majority of the cases where the loop is present.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".