Intraoral incision for mandibular angle reduction osteoplasty under endoscope
Bibliographic record
Abstract
Objective Due to structural limitations,surgical vision and operation of space is more limited,we hope that with endoscopic techniques to explore a kind of operating under direct vision method of mandibular angle plastic surgery though intraoral approach.Methods Design drawing lines,grinding thinning outer mandibular plates,curved hypertrophy of the mandibular angle resection and slope trimming marginal mandibular was employed for prominent mandibular angle though intraoral approach under endoscope so that the mandible in the three-dimensional reduced.Results Since 2005,256 cases whe were subject to prominent mandibular angle underwent curved mandible angle osteotomy though intraoral approach under endoscope.All cases gained more beautiful facial contour.Conclusion ① full-mouth incision into the road surface will not leave behind any traces of surgery.②endoscopic design drawing lines,accurate and symmetry;surgical operations were carried out under direct vision,safe and reliable.③surgical removal of hypertrophy of the jaw with curved angle,so that the natural curvature of the mandibular angle perfect;complete mandibular thinning outer plate so that the integrity of the front face reduced;fine finishing marginal mandibular,so that the entire lower jaw is more smooth contours of soft parts,which face the middle and lower parts of three-dimensional to effectively narrowed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".