Comparison of positioning errors on panoramic radiographs in Indonesian children, adults, and elderly patients
Bibliographic record
Abstract
Introduction: Panoramic radiography is one of the most frequently used extraoral radiography techniques.Different anatomical structures and levels of understanding of instructions may differ in different age groups.Objectives: To investigate the distribution of positioning errors on panoramic radiographs and their correlation between the age groups of children, adults, and the elderly.Material and methods: This descriptive cross-sectional study used 495 panoramic radiographs from oral radiology medical records at a dental hospital.The inclusion criteria were 3 age categories; children (≤ 14 years), adults (15-59 years), and the elderly (≥ 60 years) selected by a consecutive sampling method.Pearson's c 2 categorical comparative statistical tests were performed for data analysis from more than 2 unpaired samples.Results: Among the 3 age groups, the radiographs that had the most errors were the children's age group, with 321 errors (37%), while the radiographs of adults and the elderly had 255 (29.4%) and 292 errors (33.6%), respectively.It was recorded that the spine not being in the upright position, improper positioning of the tongue, and moving during exposure were statistically significantly different between the children, adults, and the elderly (p < 0.05, Pearson's c 2 test). Conclusions:The results of this study showed that the most common error in the 3 age groups was incorrect tongue position.In elderly patients, the position of the spine was the second most common error, while in children, it was moving during exposure.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".