Tongue reconstruction: Rebuilding mobile three‐dimensional structures from immobile two‐dimensional substrates, a fresh cadaver study
Bibliographic record
Abstract
OBJECTIVE: To determine the two-dimensional (2D) characteristics of flaps necessary to create three-dimensional (3D) tongue anatomy. METHODS: Dissection of 11 fresh, nonpreserved human cadavers was performed. Six defects in each were created: total tongue, total oral tongue, hemiglossectomy, oral hemiglossectomy, total base of tongue, and hemi-base of tongue. The resections were debulked to create flat, 2D mucosal flaps. The dimensions and shapes of these flaps were determined. RESULTS: Each specimen showed consistent dimensions and geometry between cadavers. The total tongue was pear-shaped, the total oral tongue was egg-shaped, the oral hemi-tongue was bullet-shaped, the hemi-tongue resembled a dagger, the total base of tongue was rectangular, and the hemi-base of tongue was hour-glass shaped. CONCLUSION: Typical dimensions and shapes of common tongue defects were determined. It is conceivable that customizing reconstructive flaps based on these data will increase the accuracy of neo-tongue reconstruction, and thus, improve functional outcomes.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".