Lamb Head as a Training Model for Septoplasty and Rhinoplasty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Septoplasty and rhinoplasty are difficult operations to learn and teach. Many modalities have been proposed to make the teaching process of these operations easier. In this study, it was investigated if lamb heads were good training models to teach septoplasty and rhinoplasty to trainees or experienced surgeons. In the first part of the study, 21 lamb heads were dissected according to a dissection protocol and several anatomical distances were measured to compare them with human cadavers. In the second part, eight lamb heads were dissected and different preservation rhinoplasty techniques were practiced. The study on 21 lamb heads used showed that the lateral crura were 17.8 × 11.6, the average interdomal distance was 8.1 mm, and the average domal width was 3.7 mm. The average length of the upper lateral cartilages was 31.1 mm laterally and 21.2 medially. The average length of the nasal bones was 63.9 mm, and the width was 16 mm. In the second part of the study, 8 lamb heads were used to experience where high-strip techniques were used in 5 and the Cottle technique in 3. This study revealed that lamb heads should be considered as an excellent training model for septoplasty and rhinoplasty. Its very low cost, ease of availability, and close similarity to the human cadavers can be counted as the main advantages. This study also proved that it was not only a tool for beginners, but also a very helpful tool for experienced surgeons to try new methods.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it