Effect of Loading Angles on Abutment Screw Loosening: In Vitro Study
Bibliographic record
Abstract
AIM: Biomechanical performance is a critical factor in the long-term success of dental implants, with abutment screw loosening being a common clinical issue. This study aimed to examine the impact of abutment screw design and external load loading angles on abutment screw loosening. MATERIALS AND METHODS: Abutments and abutment screws with 30°, 60°, 90°, and 180° fitting tapers were fabricated and tested for preload and initial loosening torque. Subsequently, dynamic loosening tests were conducted at loading angles of 15°, 30°, and 45°. Finite element analysis (FEA) was used to calculate the stress and strain distribution of the abutment screws. RESULTS: The findings indicated that large-taper abutment screws exhibit a higher preload, whereas small-taper abutment screws demonstrate greater loosening torque values. Additionally, as the loading angle increases, the loosening torque value decreases, and the stress and strain values of the abutment screw increase. CONCLUSIONS: Abutment screws with smaller taper heads exhibited superior resistance to loosening. Moreover, the anti-loosening performance of the abutment screws decreased with higher external load loading angles.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".