Muscle fiber diameter assessment in cleft lip using image processing
Bibliographic record
Abstract
OBJECTIVE: To pilot investigation of muscle fiber diameter (MFD) on medial and lateral sides of the cleft in 18 infants with cleft lip with or without cleft palate (CL/P) using image processing. MATERIAL AND METHODS: Formalin-fixed paraffin-embedded (FFPE) tissue samples from the medial and lateral sides of the cleft were analyzed for MFD using an image-processing program (ImageJ). For within-case comparison, a paired Student's t test was performed. For comparisons between classes, an unpaired t test was used. RESULTS: Image processing enabled rapid measurement of MFD with majority of fibers showing diameter between 6 and 11 μm. There was no significant difference in mean MFD between the medial and lateral sides, or between CL and CLP. However, we found a significant difference on the medial side (p = .032) between males and females. CONCLUSION: The image processing on FFPE tissues resulted in easy quantification of MFD with finding of a smaller MFD on the medial side in males suggesting possible differences in orbicularis oris (OO) muscle between the two sexes in CL that warrants replication using larger number of cases. Moreover, this finding can aid subclinical phenotyping and potentially in the restoration of the anatomy and function of the upper lip.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".