The association between dietary zinc intake and risk of pancreatic cancer: a meta-analysis
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
Previous reports have suggested a potential association on dietary zinc intake with the risk of pancreatic cancer. Since the associations between different studies were controversial, we therefore conducted a meta-analysis to reassess the relationship between dietary zinc intake and pancreatic cancer risk. A comprehensive search from the databases of PubMed, Embase, Web of Science, and Medline was performed until January 31, 2017. Relative risk (RR) with 95% confidence intervals (CI) derived by using random effect model was used. Sensitivity analysis and publication bias were conducted. Our meta-analysis was based on seven studies involving 1659 cases, including two prospective cohort studies and five case–control studies. The total RR of pancreatic cancer risk for the highest versus the lowest categories of dietary zinc intake was 0.798 (0.621–0.984), with its significant heterogeneity among studies (I2=58.2%, P=0.026). The average Newcastle–Ottawa scale (NOS) score was 7.29, suggesting a high quality. There was no publication bias in the meta-analysis about dietary zinc intake on the risk of pancreatic cancer. Subgroup analyses showed that dietary zinc intake could reduce the risk of pancreatic cancer in case–control studies and among American populations. In conclusion, we found that highest category of dietary zinc intake can significantly reduce the risk of pancreatic cancer, especially among American populations.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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