Endoscopic Diagnosis and Treatment of Superficial Esophageal Squamous Cell Cancer: Present Status and Future Perspectives
Bibliographic record
Abstract
This review provides information regarding the preoperative examinations, indications for endoscopic resection (ER), and curability assessment in subjects with superficial esophageal squamous cell carcinoma (SCC). Narrow-band imaging (NBI) is a more sensitive modality for detecting esophageal cancer than conventional observation, and esophageal observation using NBI is thus recommended for the detection of superficial esophageal cancer. It is also important to adjust the volume of air in the esophagus during observation. Workup by non-magnifying followed by magnifying endoscopy is a common process for diagnosing the invasion depth of superficial esophageal SCCs in Japan. Endoscopic ultrasonography carries a risk of overdiagnosis, and its routine use is therefore not recommended. The Japanese endoscopic submucosal dissection/endoscopic mucosal resection guidelines for esophageal cancer considered the indications for ER based on the results of studies focusing on clinical MM/SM1 cancers, and concluded that clinical MM/SM1 carcinomas, except circumferential carcinoma, were an indication for ER. The curative effect of ER should be assessed based on histologic examination of the resected specimens. ER should be conducted based on a thorough understanding of the preoperative diagnosis, indication, curability, and additional treatment of esophageal SCC.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".