Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide an overview of the field of pancreatoscopy and to summarize the data informing its clinical utility. RECENT FINDINGS: Regarding the technological advance of pancreatoscopy, recent studies are the first to report the use of digital, single-operator pancreatoscopy (SpyGlass DS; Boston Scientific, Natick, MA). New data on the use of preoperative pancreatoscopy offer promising results for the potential to optimize treatment of intraductal papillary mucinous neoplasms and to differentiate between benign and malignant pancreatic strictures. Finally, there has been accumulating evidence for the use of pancreatoscopy-guided lithotripsy for the management of painful chronic calcific pancreatitis. SUMMARY: Endoscopic pancreatoscopy offers the advantage of direct visualization of the pancreatic duct, allowing for optimal macroscopic assessment, targeted tissue acquisition and guided therapies such as lithotripsy of pancreatic duct stones. The data informing some aspects remain limited, but the accumulating literature forms our understanding of the current and future role of pancreatoscopy in the management of pancreatic disease.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".