Bibliographic record
Abstract
I was very interested by the study by Barrie and Klein recently published in Endoscopy [ 1 ], as it describes a very simple and apparently innocuous method of improving cannulation in endoscopic retrograde cholangiopancreatography (ERCP). I would, however, like to point out that the authors did not mention the depth of sedation (light, moderate, or anesthesia), or the drugs used to sedate the patients in the study (some drugs used in sedation for ERCP have a potential to cause contraction of the sphincter of Oddi), or whether the sedation was administered by an anesthesiologist. I would also like to point out that the clear liquid meals ingested 2 h before elective procedures requiring general anesthesia, as recommended by the American Society of Anesthesiology, are intended for children, and that the liquid meal used in the study was intentionally a fatty liquid meal and not a clear liquid one. I think that such details should be clarified, as this is a potentially very interesting method that could be used in a more generalized fashion in most ERCP examinations.
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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.047 | 0.031 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".