Histological Evaluation of Acute Covering of an Experimental Neural Tube Defect with Biomatrices in Fetal Sheep
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to determine the histological effect on the neural tissue of in utero covering of an experimental neural tube defect in fetal lambs, with the use of two different biomatrices. MATERIALS AND METHODS: In 23 fetal sheep, surgery was performed at 79 days' gestation. In 19 of these, a neural tube defect was created, while 4 fetuses served as sham-operated controls. In 7 of the 19 operated fetuses the defect was left uncovered. In the remaining 12 animals the defect was covered either with a collagen biomatrix (4 animals), skin (3 animals), or small intestinal submucosa biomatrix (5 animals). The lambs were sacrificed at 1 week of age and histological examination was performed. RESULTS: All lambs with an uncovered neural tube defect showed histological damage of the spinal cord. In lambs in which the neural tube defect was covered, one half showed a normal architecture of the spinal cord while minor histological damage was present in the other half. Between the three groups in which the defect was covered, the histological outcome was comparable. CONCLUSIONS: Acute covering of an experimental neural tube defect in fetal lambs prevents severe histological damage to the spinal cord independent of the two biomatrices used in this study.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".