Endoscopic diagnosis and treatment of early esophageal squamous neoplasia
Bibliographic record
Abstract
Esophageal cancer is one of the leading causes of cancer-related death and is associated with high morbidity and mortality. It carries a poor prognosis as more than half of patients present with advanced and unresectable disease. One contributing factor is the increased risk of lymph node metastases at early stages of disease. As such, it is essential to detect squamous cell neoplasia (SCN) at an early stage. In order to risk stratify lesions, endoscopists must be able to perform image enhanced endoscopy including magnification and Lugol's chromoendoscopy. The assessment of both the horizontal extent and depth of any lesion is also of utmost importance prior to treatment. Endoscopic mucosal resection and submucosal dissection remain the standard of care with literature supportive their respective use. Radiofrequency ablation and other endoscopic treatments are currently available although should not be considered first line at this time. Our objective is to review the current options for the endoscopic diagnosis and treatment of esophageal SCN.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".