Cleft Lip, Cleft Palate, and Velopharyngeal Insufficiency
Bibliographic record
Abstract
In Brief Learning Objectives: After reading this article, the participant should be able to: 1. Recognize the clinical features associated with unilateral cleft lip, bilateral cleft lip, the cleft lip nasal deformity, cleft palate, and velopharyngeal insufficiency. 2. Describe the most frequently used techniques for repair of cleft lip and palate. 3. Diagnose and treat velopharyngeal insufficiency. Summary: This article provides an introduction to the anatomical and clinical features of the primary deformities associated with unilateral cleft lip–cleft palate, bilateral cleft lip–cleft palate, and cleft palate. The diagnosis and management of secondary velopharyngeal insufficiency are discussed. The accompanying videos demonstrate the features of the cleft lip nasal deformities and reliable surgical techniques for unilateral cleft lip repair, bilateral cleft lip repair, and radical intravelar veloplasty. RELATED VIDEO CONTENT IS AVAILABLE ONLINE.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".