Current research status of endoscopic submucosal dissection for colorectal neoplasms
Bibliographic record
Abstract
Endoscopic submucosal dissection (ESD) has been applied to, and gradually standardized for, early gastric cancers; however, it has not yet been widely used for treatment of colorectal neoplasms. Compared with gastric ESD, the thinner colorectal wall and winding nature of the colon make colorectal ESD a much more difficult operative technique. Despite greater risks of postoperative complications, particularly perforation of the colon, more and more endoscopists are making an effort to study this new technique in terms of its capability of larger neoplastic resection, higher en bloc resection rate and lower local recurrence rate of neoplasms in comparison with other endoscopic treatments. Thus, colorectal ESD may become the standard treatment for early colorectal neoplasms in the future. This review article discusses the current research on endoscopic submucosal dissection for colorectal neoplasms. Please see supplementary files for the accompanying video ESD with snare.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".