Advanced Imaging Technologies for the Detection of Dysplasia and Early Cancer in Barrett Esophagus
Bibliographic record
Abstract
Advanced esophageal adenocarcinomas arising from Barrett esophagus (BE) are tumors with an increasing incidence and poor prognosis. The aim of endoscopic surveillance of BE is to detect dysplasia, particularly high-grade dysplasia and intramucosal cancers that can subsequently be treated endoscopically before progression to invasive cancer with lymph node metastases. Current surveillance practice standards require the collection of random 4-quadrant biopsy specimens over every 1 to 2 cm of BE (Seattle protocol) to detect dysplasia with the assistance of white light endoscopy, in addition to performing targeted biopsies of recognizable lesions. This approach is labor-intensive but should currently be considered state of the art. Chromoendoscopy, virtual chromoendoscopy (e.g., narrow band imaging), and confocal laser endomicroscopy, in addition to high-definition standard endoscopy, might increase the diagnostic yield for the detection of dysplastic lesions. Until these modalities have been demonstrated to enhance efficiency or cost effectiveness, the standard protocol will remain careful examination using conventional off the shelf high-resolution endoscopes, combined with as longer inspection time which is associated with increased detection of dysplasia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".