Obesity and cancer, a case for insulin signaling
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
Obesity is a worldwide epidemic, with the number of overweight and obese individuals climbing from just over 500 million in 2008 to 1.9 billion in 2014. Type 2 diabetes (T2D), cardiovascular disease and non-alcoholic fatty liver disease have long been associated with the obese state, whereas cancer is quickly emerging as another pathological consequence of this disease. Globally, at least 2.8 million people die each year from being overweight or obese. It is estimated that by 2020 being overweight or obese will surpass the health burden of tobacco consumption. Increase in the body mass index (BMI) in overweight (BMI>25 kg/m(2)) and obese (BMI>30 kg/m(2)) individuals is a result of adipose tissue (AT) expansion, which can lead to fat comprising >50% of the body weight in the morbidly obese. Extensive research over the last several years has painted a very complex picture of AT biology. One clear link between AT expansion and etiology of diseases like T2D and cancer is the development of insulin resistance (IR) and hyperinsulinemia. This review focuses on defining the link between obesity, IR and cancer.
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) | 0.000 | 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