A Concrescence between Second and Third Molars
Bibliographic record
Abstract
Background: Concrescence is a rare dental anomaly in which juxtaposed teeth are united in the cementum but not in the dentin. The incidence of Concrescence teeth is reported to be highest in the posterior maxilla. It often involves a second molar with roots in near proximity to those of a third molar. It is more common on maxillary third and second molars and may be inadvertently diagnosed during a tooth extraction. Although the exact etiology of concrescence has not yet been explained, it is usually suspected that space restriction during development, local trauma, excessive occlusal force or local infection after development play an important role. Unexpected complications arising from the concrescence may lead to legal issues. Case Report: Extracting right maxillary second molar in a 33-year-old female patient with a chief complaint of toothache in a right maxillary second molar. It became evident that the second and third molars were attached between the roots. So both teeth were extracted a traumatically and healing was uneventful. Conclusion: In fact, concrescence is not common anomaly, so the clinician should always consider it, especially in the case of maxillary molars, and the patient should be informed about its complications. A small fused area may be separated during the extraction. But a broader connected area (like in this case) may lead to the extraction of both involved teeth.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".