Comparison of porcelain veneers and crowns for resolving esthetic problems: two case reports.
Bibliographic record
Abstract
�hen dentists are considering restoration of maxillary anterior teeth to improve esthetics, they must often choose between porcelain ven eers and full-coverage crowns. Porcelain veneers are considered much more conservative in terms of the requirements for preparation, and they provide satisfactory, long-lasting esthetic results. Typically only the facial surface is involved in veneer preparation, with the minimal preparation depth ranging from 0.3 to 0.5 mm to maintain the all-enamel surface that is necessary for optimum bonding to the veneers. 1 However, if the teeth are already compromised by the presence of extensive carious lesions, wear, old restorations or endodontic treatment, placement of a crown is the more prudent choice. This article presents 2 selected cases, one illustrating an ideal situation for veneer restorations and the other illustrating an ideal situation for crowns. Case � 1 � A 60-year-old woman presented with the chief complaint of anterior teeth that
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".