Diabetes, Insulin Use, and Cancer Risk: Are Observational Studies Part of the Solution–or Part of the Problem?
Bibliographic record
Abstract
Cancer has overtaken cardiovascular disease asthe leading cause of death in individuals underthe age of 65 in the general population, but it isstill overshadowed by cardiovascular disease in those with diabetes. People with type 2 diabetes are nonetheless more likely to develop cancer—and to die from it—than members of the general population, so cancer should be numbered among the complications of diabetes (1). Furthermore, the number of cancer victims with diabetes will inevitably rise in proportion to our success in combating vascular disease in the diabetic population. How can the increased cancer risk in diabetes be explained? To begin with, it should be noted that obesity, insulin resistance, and/or increased levels of IGF-1 and insulin are strongly associated with most (but not all) of the diabetes-related cancers in the nondiabetic population (1). This suggests that hyperglycemia does not play an
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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 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.028 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 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".