Dental 3D-Printing: Transferring Art from the Laboratories to the Clinics
Bibliographic record
Abstract
The rise of three-dimensional (3D) printing technology has changed the face of dentistry over the past decade. 3D printing is a versatile technique that allows the fabrication of fully automated, tailor-made treatment plans, thereby delivering personalized dental devices and aids to the patients. It is highly efficient, reproducible, and provides fast and accurate results in an affordable manner. With persistent efforts among dentists for refining their practice, dental clinics are now acclimatizing from conventional treatment methods to a fully digital workflow to treat their patients. Apart from its clinical success, 3D printing techniques are now employed in developing haptic simulators, precise models for dental education, including patient awareness. In this narrative review, we discuss the evolution and current trends in 3D printing applications among various areas of dentistry. We aim to focus on the process of the digital workflow used in the clinical diagnosis of different dental conditions and how they are transferred from laboratories to clinics. A brief outlook on the most recent manufacturing methods of 3D printed objects and their current and future implications are also discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".