Revolutionizing small bowel transplantation in mice and rats: A cutting-edge dry-lab simulation model
Bibliographic record
Abstract
Background Animal reduction is a key ethical goal in research. Small bowel transplantation in rodents is essential for studying rejection but training consumes many animals without scientific yield. Methods We developed a low-cost simulation model using silicone-coated intravenous lines sized to mouse vasculature (SMA, portal vein, aorta, vena cava). Eight experienced microsurgeons performed anastomoses and rated usability, similarity, and material quality (5-point Likert). Results The model allowed realistic training in suturing and vessel handling. Arterial components mimicked tissue well, while venous models were overly rigid. Usability was rated high, procedural similarity moderate–positive. Suturing and procedure times resembled live surgery, though haptic feedback and knot security were limited. Conclusion This reproducible dry-lab model supports early microsurgical training and reduces animal use. Despite material limitations, it provides a practical, ethical tool for foundational skill development.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".