Endoscopic Web Localization for Laparoscopic Duodenal Web Excision
Bibliographic record
Abstract
When performing an open duodenal web excision, it is helpful to identify the web using a nasogastric tube because it is often difficult to determine where the web origin is located when looking at the serosal side of the bowel. However, it may be challenging to navigate the nasogastric tube to the web during laparoscopy. We present a novel technique that utilizes intraoperative endoscopy to precisely identify the location of the duodenal web, facilitating laparoscopic excision. Intraoperative endoscopy was implemented in the case of a 3-month-old boy undergoing laparoscopic excision of a duodenal web. With endoscopic visualization and transillumination, the duodenal web was precisely identified and excised laparoscopically. A supplemental video of the case presentation and technique is provided in the online version of this manuscript (Supplemental Digital Content 1, http://links.lww.com/SLE/A134). The procedure was completed successfully and the patient did well postoperatively. Flexible endoscopy is a useful adjunct for duodenal web localization during laparoscopy, improving on the previous method of estimating the location based on a change in duodenal caliber.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".