Bibliographic record
Abstract
The upper face, including the eyebrows and periorbital regions, plays a dynamic role in the aging face. With the natural process of aging, the position of the brow relative to the supraorbital rim may become ptotic. Commonly, this presents as excessive hooding of the lateral eyelid but, in severe cases, may result in a visual field obstruction. Other less common causes of this phenomenon may be due to acquired facial paralysis or secondary to post-traumatic deformity. Various surgical options exist to reposition the brow, ranging from traditional open techniques to newer endoscopic approaches. Each of these techniques has their respective strengths and weaknesses, but no individual procedure has proven superiority in all clinical scenarios. Recently, there have been trends in aesthetic surgery towards the utilization of the endoscopic browlift technique. Nevertheless, traditional open approaches remain a fundamental skill in the armamentarium of the facial surgeon as it provides the greatest degree of accuracy in relation to brow repositioning. Herein we outline the nuances of one of these open approaches, the direct brow lift, and focus on its role in rejuvenating the upper third of the face.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".