Biological Evaluation of Implant Drill Made from Zirconium Dioxide
Bibliographic record
Abstract
PURPOSE: Zirconia is a good candidate material in the dental field. In this study, we evaluated biological responses against a zirconia drill using a bone cavity healing model. MATERIALS AND METHODS: Zirconia drills, stainless steel drills, and the drilled bone surface were observed by scanning electron microscopy (SEM), before and after cavity preparation. For the bone cavity healing model, the upper first and second molars of Wistar rats were extracted. After 4 weeks, cavities were prepared with zirconia drills on the left side. As a control, a stainless steel drill was used on the right side. At 3, 7, and 14 days after surgery, micro-CT images were taken. Samples were prepared for histological staining. RESULTS: SEM images revealed that zirconia drills maintained sharpness even after 30 drilling procedures. The bone surface was smoother with the zirconia drill. Micro-CT images showed faster and earlier bone healing in the zirconia drill cavity. On H-E staining, at 7 days, the zirconia drill defect had a smaller blank lacunae area. At 14 days, the zirconia drill defect was filled with newly formed bone. CONCLUSIONS: The zirconia drill induces less damage during cavity preparation and is advantageous for bone healing. (197 words).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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 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".