Evaluation of sheep sinonasal endoscopic anatomy as a model for rhinologic research
Bibliographic record
Abstract
OBJECTIVES: Despite many publications describing sheep models for functional endoscopic sinus surgery (FESS) procedures, accurate endoscopic anatomical studies are lacking. There are no publications correlating computed tomography (CT) and 3D models with endoscopic anatomical descriptions. This study evaluates and describes the endoscopic anatomy of a sheep model. METHODS: Ten live sheep (20-sides) were included. Two cadaveric specimens, imaged using thin slice CT for 3D reconstruction correlation were also included. Using endoscopy, anatomical structures were measured and described. Measurement of the same structures was carried out using the 3D imaging model. RESULTS: Three sets of turbinates were identified at 2.3, 5.1 and 8.5 cm from the anterior nasal sill. Frontal recess and uncinate process were identified at 12.7 cm. The septum has a bony and cartilaginous component and measures 10.5 cm. The sphenopalatine foramen was measured at 12.1 cm. All anatomical measurements were correlated with the measurements on the CT scan 3D volume-rendering model, thereby allowing for an accurate description of the sheep sinonasal anatomy. CONCLUSION: This study describes the endoscopic sinonasal anatomical measurements of the adult sheep. It is the first study to evaluate the sheep CT and endoscopic anatomy in order to determine its feasibility as an animal model for research in FESS.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".