3D Comparative Evaluation of Condylar Morphology Between Chronic Areca Nut Chewers and Nonchewers: Protocol for a Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Areca nut (AN) is a commonly consumed psychoactive substance, especially in South and Southeast Asia. Chronic chewing of AN has been linked to multiple health problems, including temporomandibular joint (TMJ) disorders. Excessive strain on TMJ during chronic AN chewing can lead to repetitive injury, resulting in microtrauma and macrotrauma to both the TMJ and the surrounding masticatory structures. Previous studies have reported the long-term impact of AN chewing on TMJ by using conventional 2D imaging. OBJECTIVE: This study aims to evaluate and compare condylar morphology in chronic AN chewers and nonchewers by using 3D imaging. METHODS: This study will include 90 patients who will be divided into 2 groups: chronic AN chewers (n=45, 50%) and nonchewers (n=45, 50%). The study will be undertaken after obtaining institutional ethics committee approval and written informed consent from each patient. A detailed habit history of all the participants will be recorded. Each patient will undergo a clinical examination and radiographic evaluation of condylar morphology. Condylar morphology will be evaluated using cone beam computed tomography scans in both sagittal and coronal planes. All the findings will be recorded and then examined for statistical significance. RESULTS: On comparison of condylar morphology between chronic AN chewers and nonchewers by using cone beam computed tomography, statistical variations relevant to structural and pathological alterations such as osteophytes, surface flattening, and erosions are likely to occur. CONCLUSIONS: This study aims to overcome the limitations of conventional 2D radiography and provide a more accurate assessment of condylar morphology. The findings should fill an existing gap in the literature by providing useful insights on the effects of chronic AN chewing on condylar structure by using 3D imaging. This research may help to improve the diagnosis, prevention, and management of TMJ disorders. TRIAL REGISTRATION: Clinical Trials Registry-India CTRI/2025/06/088238; https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=MTMzNzQz&Enc=&userName=. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/84038.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".