The art of minimal tooth reduction for veneer restorations
Bibliographic record
Abstract
Abstract Minimal tooth reduction is crucial for the long-term success of adhesive restorations. It has been proven that bonding to enamel is more predictable in obtaining better long-term success than dentin due to its higher percentage of mineral content. The diagnostic wax-up and subsequent mock-up are the first diagnostic tools available to evaluate discrepancies between current and ideal tooth proportions. The intraoral mock-up provides the patient a tactile and visual evaluation of the size, shape, and shade of the proposed final restorations, and at the same time, the clinician can evaluate the smile line, lip support, phonetics, and occlusion. During the tooth preparation, the mock-up provides a reduction guide to the clinician to achieve the minimal required reduction for the final restoration avoiding the over-reduction and dentin exposure. This clinical report shows feldspathic veneer restorations provided with conservative tooth preparation. The long-term success of the restoration requires following well-defined protocols for restorative material selection, conservative tooth preparation, total isolation with rubber dam, and bonding ceramic protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".