In Vitro Assessment with the Infrared Thermometer of Temperature Differences Generated During Implant Site Preparation: The Traditional Technique Versus the Single‐Drill Technique
Bibliographic record
Abstract
PURPOSE: To assess in vitro, using an infrared (IR) thermometer, temperature changes generated at implant sites by osteotomies involving two different drilling methods (with multiple drills versus only one) and to measure the influence of irrigation on the temperature variation. MATERIALS AND METHODS: Forty bone samples (from bovine rib) were divided into two groups of 20. Osteotomies were performed in group A with four drills, using the standard method (Leone Dental Implant System, final diameter 3.5 mm), and in group B with a single drill (Zero1 Drill, Leone Dental Implant System 3.5 mm diameter). In each group, half of the osteotomies were performed with irrigation (subgroups A1 and B1) and the other half without irrigation (subgroups A2 and B2). Two osteotomies were performed on each sample, using four different-sized drills according to the standard technique on one side and using a single drill on the other side. The starting temperature (T0 ) and the maximum temperature (Tmax ) reached in the bone were measured. Comparisons of ΔT were drawn between subgroups A1 and B1 and between subgroups A2 and B2. The data were analyzed using Student's t-test (with 95% confidence interval). RESULTS: The mean difference identified between the temperature produced with the last drill used in the traditional technique and that produced with the single drill was 0.3150 ± 1.0194°C when irrigation was used (group A1 vs group B1; not statistically significant). The mean difference between the temperature produced with the last drill of the traditional technique and that produced with the single drill was -0.3526 ± 0.5232°C when irrigation was not used (group A2 vs group B2; statistically significant). CONCLUSIONS: The single-drill method induced a significantly greater variation in temperature than the traditional method, but only when irrigation was used; without any irrigation, the difference in the temperature variation generated by the two methods was not statistically significant. In any case, bone heating during the osteotomy never exceeded 2°C and was clinically irrelevant, as thermal damage to bone has only been reported in the literature for temperatures beyond 47°C persisting for more than one minute.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| 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".