Bibliographic record
Abstract
Dr Nabil Fanous presented a clear discussion of his theory of the intrinsic mobility of the face. The author noted that the mobility of the superficial musculoaponeurotic system (SMAS) layer is more dominant than the subskin layer. This is an astute observation and has inherent practical applications. The concept of calling this mobility ‘intrinsic’ is a good one. The author dramatically and pictorially described the technique for the preoperative markings. It would have been easier to follow had he used the same side of the face for his diagrams and photographs. The description and intraoperative presentation of his suturing technique was very clear. The author compared the various techniques currently used in achieving facelift surgery. He concluded that it is not always necessary to have an extensive dissection to achieve the end result. This of course is an axiom for all surgery – do no more dissection than required to achieve the end result, whether you are doing a facelift or a fasciectomy for Dupuytren’s contracture. Dr Fanous’ technique of SMAS plication is similar to the less invasive suturing plications of the SMAS that are being presented currently. The author documented the historical evolution of SMAS anatomy and utilization. One must not forget that, 45 years ago, Dr Gustof Aufricht was hauling up and suturing the SMAS – he called it the deep fascia. The pre- and postoperative photographs depicting the results were comparably clear; all of the patients presented had a loose integumentary system. The results were good and demonstrated that what could be achieved from plications of the SMAS only and lateral placation of the platysma only. The author did not show any patients with heavy integumentary systems or fat necks, which would require suction-assisted lipectomy and subplatysma removal of fat.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".