Implant supported prosthetic rehabilitation following complete exodontia - case report
Bibliographic record
Abstract
INTRODUCTION: This case report presents the fabrication of mandibular implant supported hybrid prosthesis in the form of a Toronto bridge hybrid bar on a metal base with acrylic teeth to rehabilitate an edentulous patient. CASE REPORT: This article describes and illustrates the 2-stage surgical and prosthetic treatment of a patient with an edentulous mandible opposing teeth of fixed dental restauration. Initially, mandibular teeth in the terminal stage of periodontitis disease were extracted. Then a temporary complete denture was made. After three months (early placement of implants after tooth extractions with partial bone healing), prosthetically- guided placement of 6 implants in the lower jaw was performed. After the period of osseointegration (protocol of conventional loading of implants) and 2 weeks after placing the healing abutment, we started the prosthetic phases (analog impression techniques). Also, this report includes the steps involved in the prosthodontic rehabilitation; an effective treatment plan, the restoration of vertical dimension, an immediate denture, an implant-level impression, a verified-master cast, the fabrication of definitive prosthesis. CONCLUSION: The prosthetic rehabilitation of a fully edentulous mandible treated with dental implants using the “Toronto Bridge” technique is effective for restoring both function and aesthetics.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".