Frequency of congenitally missing third molars in orthodontic patients.
Bibliographic record
Abstract
Objective: To determine the frequency of congenitally missing third molars in Orthodontic patients. Study Design: Retrospective Study. Setting: Department of Orthodontics at Abbottabad International Dental College, Abbottabad. Period: February 2021 to November 2021. Material & Methods: Retrospective data was collected from the files in the departmental archives. Files from the past seven years were studied for data collection. Congenitally missing teeth were identified from the patient’s history and the Orthopantomogram present within each file. The collected data was analyzed via SPSS software Version 21. Results: Chi-square test was applied to find the frequency of missing teeth. Congenital absence of third molars was highly significant among maxilla and mandible (p-value <0.001). No significant difference was found among the genders. Conclusion: Congenitally missing third molars are more prevalent in the maxilla than the mandible.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".