Guidelines for endoscopic treatment of postinflammatory pancreatic and peripancreatic fluid collections
Bibliographic record
Abstract
DOI: 10.20452/wiitm.2025.17987, Published online: December 29, 2025, Authors: Mateusz Jagielski, Marian Smoczyński, Anna Wiechowska‑Kozłowska, Jacek Sobocki, Grażyna Rydzewska‑Wyszkowska, Krystian Adrych, Andrzej Baniukiewicz, Andrzej Białek, Jarosław Daniluk, Małgorzata Degowska, Jacek Drzewiecki, Michał Dubowik, Adam Durczyński, Łukasz Durko, Marek Durlik, Anita Gąsiorowska, Piotr Gietka, Stanisław Głuszek, Stanisław Hać, Piotr Hogendorf, Roman Kaczor, Michał F. Kamiński, Dariusz Kąkol, Sławomir Kozieł, Łukasz Krupa, Michał Kukla, Krzysztof Kurek, Katarzyna Kuśnierz, Tomasz Marek, Ewa Małecka‑Wojciesko, Janusz Milewski, Sławomir Mrowiec, Ewa Nowakowska‑Duława, Katarzyna M. Pawlak, Jan Pertkiewicz, Michał Pędziwiatr, Marcin Polkowski, Michał Pracki, Adam Przybyłkowski, Artur Raiter, Jarosław Reguła, Piotr Richter, Jerzy Sieńko, Maciej Słodkowski, Maciej Słupski, Michał Spychalski, Robert Staroń, Jacek Szeliga, Mirosław Szura, Wiesław Tarnowski, Grzegorz Wallner, Renata Talar‑Wojnarowska, Krzysztof Zieniewicz, Michał Żorniak, Marek Jackowski
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.018 |
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".