Clinical performance of a modified Resin‐Bonded fixed partial denture (Carolina bridge): A retrospective study
Bibliographic record
Abstract
OBJECTIVES: This research aims to retrospectively evaluate the clinical performance of Carolina bridge (CB) placed at a dental school. MATERIALS AND METHODS: Data were collected from the electronic patient record system. A follow-up letter was sent to the subjects' mailing address explaining the research purpose along with a questionnaire to assess their satisfaction with the treatment. A phone interview was performed to assess patient satisfaction, function, and choice of permanent restoration. Finally, a clinical exam was conducted for patients that agreed to come for a follow-up and still had their CBs. RESULTS: Twenty-three patients with 26 resin-bonded CBs met the inclusion criteria. All patients who did the phone interview reported to be very satisfied with the treatment. Most chose to keep the CB as definitive treatment and not to move forward with implant therapy. According to the number of rebonding needed to maintain the CB, the types of survival were analyzed as 42.3% complete survival (no rebonding needed), 26.9% functional survival (rebonded once), 23.1% survival with multiple rebondings, 7.6% failure. CONCLUSION: The performance of CBs revealed highly acceptable performance with high-patient satisfaction. CLINICAL SIGNIFICANCE: Carolina ridge is an esthetic and conservative interim treatment option that can be utilized in favorable clinical situations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".