Initial Stability of Two Dental Implant Systems: Influence of Buccolingual Width and Probe Orientation on Resonance Frequency Measurements
Bibliographic record
Abstract
BACKGROUND: Although many factors seem to have an impact on the resonance frequency (RF) values of implants, there is a lack of evidence about some other parameters, which may have an influence on implant stability. PURPOSE: The aims of the study were to determine whether initial stability of a dental implant differs when the buccolingual width of the bone changes, to determine whether different orientations affect the RF measurements in the RF device, and to investigate two dental implants with different morphologies with regard to their initial stability. MATERIALS AND METHODS: Two implant systems (Tidal Spiral Dental Implant Systems, Huntsville, AL, USA, and MIS Seven, MIS Implants Technologies Ltd., Shlomi, Israel) with diameters of 3.75 mm and 4.2 mm and with a length of 13 mm were used. Following the insertion of implants, buccolingual thinning of the models was performed in 2-mm increments ranging between 0 and 8 mm. RESULTS: A statistically significant decrease for implant stability quotient (ISQ) values was noticed for both diameters and both systems for all dimensional time points of the blocks (p < .05). The second system (more number of threads) resulted with higher ISQ values for both diameters than the first system (lower number of threads) (p < .001). The orientation of the probe influenced the measurements, where a standard orientation is advisable for the magnetic RF device. CONCLUSION: Different implant surface geometries seem to behave in different patterns in terms of initial stability. Dimensional changes in buccolingual direction seem to have an impact on the initial stability, where wider implants also presented higher ISQ values than narrow ones.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".