Digital removable partial dentures
Bibliographic record
Abstract
Abstract Recently, digital techniques have revolutionized the production of partial removable dental prostheses (PRDPs). This chapter reviews current systems for PRDP production, how they are done in clinical practice, advantages and limitations, and current literature regarding their clinical performance. Currently, several digital techniques are available in the market for PRDP production including subtractive and additive techniques. Subtractive milling technique is mainly effective for non-metal PRDP, whereas additive techniques are used mainly in metal PRDP. Digital techniques expand the range of materials that can be utilized for PRDP production, including new polymers (PEEK), and facilitate previously difficult procedures such as casting titanium PRDP, which can be produced more easily with digital methods. This review shows that available evidence suggests that these techniques have promising clinical results. Laser sintering resulted in higher patient’s satisfaction compared to conventional PRDP. However, long-term clinical trials are recommended to explore the long-term effects of these techniques. Moreover, this review showed the lack of evidence on the clinical performance of non-metal partial removable dental prostheses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".