Temperature Changes in Cortical Bone after Implant Site Preparation Using a Single Bur versus Multiple Drilling Steps: An In Vitro Investigation
Bibliographic record
Abstract
OBJECTIVES: The study aims to test the hypothesis of no differences in temperature variation by using a single bur for implant site preparation as compared with conventional drilling sequence using multiple burs with incremental diameter. MATERIALS AND METHODS: Synthetic blocks of bone (type I density) were used for drilling procedures. THREE GROUPS WERE EVALUATED: Group 1 and Group 2 - drilling with three consecutive burs for a 4.1 mm cylindrical implant and for a 4.3 mm conical implant, respectively; Group 3 - drilling with a single bur for a 4.2 mm conical implant. For each group, 20 drilling procedures were performed without irrigation and 20 with external irrigation. The temperature in the cortical bone during osteotomy for implant site preparation was measured through a thermocouple. RESULTS: The mean temperatures and standard deviations for the drilling without irrigation were: 25.5 ± 1.24°C for Group 1; 28.1 ± 1.76°C for Group 2; 26.5 ± 1.79°C for Group 3. Considering the drilling with irrigation, the mean values and standard deviations were: 20.4 ± 1.17°C for Group 1; 22.2 ± 1.38°C for Group 2; 20.2 ± 0.83°C for Group 3. Groups 1 and 3 yielded similar results, while Group 2 displayed significantly higher temperature increase than the other two groups. CONCLUSIONS: The single bur drilling protocol did not produce greater bone heating than the conventional protocol and may be considered a safe procedure.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".