Bibliographic record
Abstract
The Pancreatobiliary Pathology Society (PBPS) wants to thank the Archives of Pathology & Laboratory Medicine for highlighting our society by publishing 4 review articles based on the presentations at the PBPS companion society symposium at the 2019 United States and Canadian Academy of Pathology (USCAP) meeting. The PBPS fosters excellence and collaboration in education, research, and the practice of pancreatobiliary pathology around the world. Although we became an official society in 2016, and a USCAP companion society in 2018, the sharing of knowledge, enthusiasm, and ideas in pancreatobiliary pathology started more than 20 years ago as an annually held “Pancreas Club” luncheon, whose first advisory council members consisted of Volkan Adsay, MD, Ralph Hruban, MD, David Klimstra, MD, Günter Klöppel, MD, and Giuseppe Zamboni, MD. Thanks to their dedication to pancreatobiliary pathology, this small club evolved into the official 501c3 society that it is today (PBPath.org).The 2019 PBPS Companion Society Symposium was titled “Challenging Topics in Pancreatic Neoplasia” and consisted of outstanding presentations including 3 talks on nonductal neoplasms of the pancreas and 1 talk on the progress of one of the PBPS's working groups, the neoadjuvant therapy working group. These talks have been converted to review articles in this issue of Archives of Pathology & Laboratory Medicine. In the first article, Laura Wood, MD, PhD, an associate professor and pancreatic pathologist who leads her own basic science laboratory at The Johns Hopkins Hospital, Baltimore, Maryland, reviews pancreatic neoplasms with acinar differentiation, along with her colleague at Johns Hopkins Hospital, Elizabeth Thompson, MD. The clinicopathologic, immunophenotypic, and molecular features of acinar cell carcinoma and pancreatoblastoma are discussed, as are the potential diagnostic pitfalls. The second article examines pancreatic neuroendocrine neoplasms and is by Laura Tang, MD, PhD, of Memorial Sloan Kettering Cancer Center, New York, New York, who has published extensively on this topic. The review includes the history, terminology, classification, and grading of these tumors, their variable morphology, differential diagnosis, and treatment. Hereditary syndromes and molecular and genomic studies in pancreatic neuroendocrine neoplasms are also discussed. Stefano La Rosa, MD, who is at the Institute of Pathology, University Hospital, Lausanne, Switzerland, along with Massimo Bongiovanni, MD, from Synlab Swiss SA (Lausanne) covers key histopathologic and genetic features of pancreatic solid-pseudopapillary neoplasm, and highlights the differences between this entity and other nonductal pancreatic neoplasms. The final review is by Huamin Wang, MD, a professor in the Department of Translational Molecular Pathology, Division of Pathology/Lab Medicine of University of Texas MD Anderson Cancer Center (MDACC), Houston, Texas, who is a funded scientist and also the chair of the neoadjuvant therapy working group of PBPS. Dr Wang, with his coauthors Teddy Sutardji Nagaria, MD, PhD, Hua Wang, MD, PhD, and Deyali Chatterjee, MD (also from MDACC and Washington University School of Medicine in St Louis, Missouri), provides a thorough review of the challenges encountered during the pathologic evaluation of treated pancreatic ductal adenocarcinoma, including its grading and staging.We are proud of our society and the contributions its members make to the field of pancreatobiliary pathology. We hope you enjoy these review articles on nonductal neoplasms and treated adenocarcinoma of the pancreas.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".