İLERİ SEVİYEDE REZORBE KRETLERE SAHİP TAM DİŞSİZ HASTANIN BAR TUTUCULU OVERDENTURE PROTEZLE REHABİLİTASYONU- OLGU SUNUMU
Bibliographic record
Abstract
Uzun süre total protez kullanan hastaların alveoler kretlerinde ileri rezorpsiyon gözlenebilmektedir. Bu hastalarda sorunların giderilmesi için implant destekli overdenturelar iyi bir alternatiftir İmplant overdenture protezlerde bar, ball (topuz), ve teleskopik tutucular gibi çeşitli tutucu sistemleri kullanılmaktadır. Bu sistemler arasında en retantif olan bar tutuculardır. Bar tutucularla implantların splintlenmesi çiğneme kuvvetlerin dağıtılması açısından yararlıdır. Bu vaka raporunda mevcut total protezinden şikayetle başvuran tam dişsiz erkek hastanın bar tutuculu implant overdenture ile tedavisi anlatılmıştır. Anahtar Kelimeler: Diş implantı; çene, dişsiz; implant-destekli protez REHABİLİTATİON OF AN EDENTULOUS PATİENT WİTH SEVERELY RESORBED RİDGES USİNG BAR RETAİNED IMPLANT OVERDENTURES- A CASE REPORT ABSTRACT Severe resorbtion of alveolar ridges can be observed in patients using complete dentures for a long time. To overcome these problems implant supported overdentures are good alternative. Various attachments systems are used for implant overdentures such as; bar, ball, magnetic and telescopic attachment systems. Among these, bar attachment system has the greatest retention. Splinting implants with bar attachments is beneficial regarding distrubution of the bite forces. In this case report an edentulous man with complaints concerning his conventional complete dentures was treated with dental implants and bar retained overdentures. Keywords: Dental implant; jaw, edentulous; implant-supported denture
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".