Brazilian oral medicine and oral pathology: international scientific collaborations
Bibliographic record
Abstract
A concern associated with implant placement is the potential occurrence of neurovascular lesions and subsequent development of sensory alterations in patients undergoing implant placements. The objective of this review is to evaluate the incidence of neurosensory alterations based on the proximity between the implant and the mandibular canal A systematic review was conducted in MEDLINE, Web of Science, and Scopus. Studies with common variables were selected to conduct a meta-analysis. The patient classification was based on the mandibular canal-implant distance. Neurosensory alteration percentages were calculated for each study and group. The findings indicate significant correlations between implant placement proximity and neurosensory risks. The incidence of neurosensory alterations in patients with implants placed at a distance ≥ 2 mm from the mandibular canal was 0%. Similarly, for distances between 1-2 mm from the mandibular canal, the incidence remained at 0%. However, for implants placed at a distance of 0-1 mm from the mandibular canal, the incidence of neurosensory alterations was 68%. Additionally, patients with implants that intruded into the canal had an incidence of 53% in the development of neurosensorial alterations. A distance of 1 mm from the mandibular canal might be safe. Implants placed at a distance less than 1 mm from the mandibular canal exhibit neurosensory alterations. Clinicians should be aware of the potential risk of nerve injury and adopt appropriate precautions, including meticulous preoperative planning and three-dimensional radiographic images.
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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.014 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.012 |
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".