Flapless dental implant surgery enabled by haptic robotic guidance: A case report
Bibliographic record
Abstract
This case report presents the use of haptic robotic technology in one patient with six implants placed in the maxilla and five implants in the lower mandible with the goal of individual single implant supported crowns to be placed over each implant after 6 months. All implants were placed using a flapless technique, with one immediate implant placement after extraction. All implants were placed with a high degree of accuracy relative to the pre-operative plan as determined by post-op CBCT analysis with an average angular deviation of 2.58° and positional deviations at the coronal and apical aspects of the implant around 1 mm (0.93 and 1.06 mm, respectively). Total surgical time of less than 2 h. Haptic robotics physically guides the location, orientation, and depth of the tools during both drilling and implantation and thus allows for accurate placement as well as the intra-operative flexibility to change the plan as necessary while providing excellent visualization and irrigation. This robotic technology provides a treatment that focuses on accuracy and safety providing the best chance at excellent surgical outcomes for the patient.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".