Intravelar and Extravelar Portions of Soft Palate Muscles in Velic Constrictions: A Three-Dimensional Modeling Study
Bibliographic record
Abstract
Purpose This study predicts and simulates the function and relative contributions of the intravelar and extravelar portions of the levator veli palatini (LVP) and palatoglossus (PG) muscles in velic constrictions. Method A finite element-based model of the 3-dimensional upper airway structures (palate, pharynx, tongue, jaw, maxilla) was implemented, with LVP and PG divided into intravelar and extravelar portions. Simulations were run to investigate the contributions of these muscles in velopharyngeal port (VPP) closure and constriction of the oropharyngeal isthmus (OPI). Results Simulations reveal that the extravelar portion of LVP, though crucial for lifting the palate, is not sufficient to effect VPP closure. Specifically, the characteristic "bulge" appearing in the posterior soft palate during VPP closure ( Pigott, 1969 ; Serrurier & Badin, 2008 ) is found to result from activation of the intravelar portion of LVP. Likewise, the intravelar portion of posterior PG is crucial in bending the "veil" or "traverse" ( Gick, Francis, Klenin, Mizrahi, & Tom, 2013 ) of the velum anteriorly to produce uvular constrictions of the OPI ( Gick et al., 2014 ). Conclusions Simulations support the view that intravelar LVP and PG play significant roles in VPP and OPI constrictions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".