Canadian National Pancreas Conference 2023: A Review of Multidisciplinary Engagement in Pancreatic Cancer Care
Bibliographic record
Abstract
Pancreatic cancer is a complex malignancy associated with poor prognosis and high symptom burden. Optimal patient care relies on the integration of various sectors in the healthcare field as well as innovation through research. The Canadian National Pancreas Conference (NPC) was co-organized and hosted by Craig's Cause Pancreatic Cancer Society and The Royal College of Physicians and Surgeons in November 2023 in Montreal, Canada. The conference sought to bridge the gap between Canadian healthcare providers and researchers who share the common goal of improving the prognosis, quality of life, and survival for patients with pancreatic cancer. The accredited event featured discussion topics including diagnosis and screening, value-based and palliative care, pancreatic enzyme replacement therapy, cancer-reducing treatment, and an overview of the current management landscape. The present article reviews the NPC sessions and discusses the presented content with respect to the current literature.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".