Effects of Drilling Technology on Mini-Implant Primary Stability: A Comparison of the Mechanical Drilling and Femtosecond Laser Ablation
Bibliographic record
Abstract
Objectives: Primary stability is a fundamental prerequisite in predicting the prognosis of a mini-implant (MI) as a skeletal anchorage. This study aims to evaluate the influence of implant site preparation technology on the primary stability of MI. Methods: A total of 108 bovine cortical bone samples were fabricated to three thicknesses (0.5, 1.0, and 1.5 mm). For each thickness group, the samples were divided into three subgroups: I (without site preparation), II (site preparation with a mechanical drill), and III (site preparation with femtosecond laser ablation). After MI insertion into these samples, the pull out strength of MI was measured by lateral pull out tests. Results: For the 0.5 mm thickness samples, the lateral pull-out strength was 9.9±2.7 N in subgroup I, 6.7±2.1 N in subgroup II, and 15.2±2.6 N in subgroup III. For the 1.0 mm thickness samples, the lateral pull-out strength was 39.3±2.5N in subgroup I, 38.2±2.7N in subgroup II, and 46.3±1.7 N in subgroup III. For the 1.5 mm thickness samples, the lateral pull-out strength was 73.9±4.8 N in subgroup I, 70.1±2.8 N in subgroup II, 75.0±2.2 N in subgroup III. No signs of carbonization or substantial cracking were visible in any of the bone samples. Conclusion: Site preparation with laser ablation significantly improved the lateral pull-out strength over mechanical preparation and control (no site preparation) in thinner cortical bone samples (1.0 and 0.5 mm). Such improvement in lateral pull-out strength decreases as the samples become thicker and diminishes in thick (1.5 mm) cortical bone samples.
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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".