The Reverse Palatal Pedicle Graft for Maxillary Molar Palatal Recessions: Two Case Reports
Bibliographic record
Abstract
INTRODUCTION: Historically, the treatment of palatal recession was thought to be extremely challenging if not impossible due to the anatomy of the palate. A novel technique is presented for treating gingival recession on maxillary molars utilizing a rotated subepithelial connective tissue pedicle graft. The technique is designed to maximize perfusion to the graft as compared to a free graft CASE PRESENTATIONS: The authors present two cases in which the technique was utilized to achieve attachment gain and root coverage. The cases were followed for at least 2 months. CONCLUSIONS: More than 5 mm of attachment was gained and 55% to 60% root coverage achieved over recession defects on maxillary first molars. The following case reports demonstrate that the Reverse Palatal Pedicle Graft (RPPG) technique was successful in improving root coverage over maxillary palatal recession defects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".