Impact of Cantilever Length on the Accuracy of Static <scp>CAIS</scp> in Posterior Distal Free‐End Regions
Bibliographic record
Abstract
BACKGROUND: Implant placement accuracy in the distal free-end posterior region is often compromised, increasing the risk of damage to adjacent anatomical structures and negatively affecting restoration function, occlusal loading, and aesthetics. OBJECTIVES: This study aimed to assess the accuracy of implant placement using static computer-assisted implant surgery (CAIS) in the posterior distal free-end partially edentulous area with varying cantilever lengths and to evaluate the correlation between cantilever length and implant deviations. MATERIALS AND METHODS: A prospective observational study involved 40 patients with 72 posterior implant sites, divided into three groups: 1-unit cantilever (1-UC; distal free-end with a mesial neighboring tooth), 2-unit cantilever (2-UC; one-tooth space from the mesial neighboring tooth), and control (single-tooth space with both mesial and distal neighboring teeth). Implants were placed using fully guided static CAIS, and accuracy was assessed by comparing angular and linear deviations at the implant platform and apex using post-operative CBCT scans. The correlation between cantilever length and implant deviations was analyzed. RESULTS: The 2-UC group exhibited significantly higher angular deviations (5.01° ± 2.41°) compared to the 1-UC (3.60° ± 1.92°, p = 0.033) and control groups (2.62° ± 1.13°, p < 0.001). The 3D deviations at both the platform and apex were also significantly greater in the 2-UC group (1.15 ± 0.38 mm, 1.74 ± 0.53 mm, respectively) than in the 1-UC (0.86 ± 0.35 mm, p = 0.001; 1.30 ± 0.47 mm, p = 0.002) and control groups (0.72 ± 0.30 mm, p < 0.001; 1.04 ± 0.38 mm, p < 0.001). Deviations in the cantilever groups predominantly trended towards the buccal and apical directions. Additionally, positive correlations were found between cantilever length and implant deviations at both the platform (R = 0.306, p = 0.034) and apex levels (R = 0.294, p = 0.042). CONCLUSION: Cantilever length in posterior implant positions significantly affects the accuracy of implant placement using static CAIS. Implants positioned at a 2-unit cantilever or with lengths exceeding 10 mm are more prone to deviating from the planned positions.
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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 | 0.005 |
| 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) | 0.002 | 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".