A proposal for the ideal algorithm for the diagnosis, staging, and treatment of pancreas masses suspicious for pancreatic adenocarcinoma: Results of a working group of the Canadian Society for Endoscopic Ultrasound
Bibliographic record
Abstract
Numerous clinical pathways exist for patients presenting with a suspicious pancreatic mass. These range from direct surgical intervention following staging, with preoperative cross-sectional imaging, EUS with or without fine-needle aspiration or fine-needle core biopsy; neoadjuvant chemotherapy and/or radiation therapy; or palliation. Although international guidelines exist for pancreas cancer management, the ideal workup and treatment for a suspicious pancreas mass is unclear. During its annual meeting in September 2017 (The Forum for Canadian Endoscopic Ultrasonography), the Canadian Society of Endoscopic Ultrasound organized a working group of experienced endosonographers and hepatobiliary surgeons from across Canada to achieve this goal.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".