Global Patterns and Trends in Pancreatic Cancer Incidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: We aim to provide a global geographical picture of pancreatic cancer incidence and temporal trends from 1973 to 2015 for 41 countries. METHODS: Joinpoint regression and age-period-cohort model was used. RESULTS: In 2012, the highest age-adjusted rate was in Central and Eastern Europe for males and North America for females. Most regions showed sex disparities. During the recent 10 years, increasing trends were observed in North America, Western Europe, and Oceania. The greatest increase occurred in France. For recent birth cohorts, cohort-specific increases in risk were pronounced in Australia, Austria, Brazil, Canada, Costa Rica, Denmark, Estonia, France, Israel, Latvia, Norway, Philippines, Republic of Korea, Singapore, Spain, Sweden, the Netherlands, United States, and US white male populations and in Australia, Austria, Brazil, Bulgaria, Canada, China, Czech Republic, Finland, France, Italy, Japan, Lithuania, Norway, Republic of Korea, Singapore, Spain, The Netherlands, United Kingdom, United States, and US white female populations. CONCLUSIONS: In contrast to the favorable effect of the decrease in smoking prevalence, other factors, including the increased prevalence of obesity and diabetes and increased physical inactivity, increased intake of red or processed meat and inadequate intake of fruits and vegetables are likely to have an unfavorable role in pancreatic cancer incidence worldwide.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it