Management of cervical external root resorption following connective tissue grafting
Bibliographic record
Abstract
BACKGROUND: Cervical external root resorption (CERR) is not a common occurrence, but can result in a hopeless tooth prognosis. Its etiology is poorly understood and its management can be challenging. The present case report describes the late presentation and management of CERR at both maxillary first premolar teeth following connective tissue grafting (CTG) procedures including use of citric acid as a chemical root surface conditioner. METHODS AND RESULTS: A 55-year-old female was diagnosed with bilateral external cervical root resorption of both maxillary first premolar teeth 28 years after CTG procedures that had included the use of citric acid root conditioning. As both teeth were asymptomatic, the patient opted for repair of the lesions via full-thickness flap elevation, meticulous removal of all granulation tissue, and restoration of the lesions with a resin-modified glass ionomer. A 2-year follow-up has been completed with no significant complications to report. CONCLUSIONS: CERR usually develops asymptomatically and is found by chance in radiographs. Its etiology is unclear, but may appear some years after soft tissue grafting to manage gingival recession. Early detection is key to be able to repair the lesions with minimal intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".