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
Excess body weight, as defined by the body mass index (BMI), has been associated with several diseases and includes subjects who are overweight (BMI ≥ 25-29.9 kg/m(2)) or obese (BMI ≥ 30 kg/m(2)). Overweight and obesity constitute the fifth leading risk for overall mortality, accounting for at least 2.8 million adult deaths each year. In addition around 11% of colorectal cancer (CRC) cases have been attributed to overweight and obesity in Europe. Epidemiological data suggest that obesity is associated with a 30-70% increased risk of colon cancer in men, whereas the association is less consistent in women. Similar trends exist for colorectal adenoma, although the risk appears lower. Visceral fat, or abdominal obesity, seems to be of greater concern than subcutaneous fat obesity, and any 1 kg/m(2) increase in BMI confers additional risk (HR 1.03). Obesity might be associated with worse cancer outcomes, such as recurrence of the primary cancer or mortality. Several factors, including reduced sensitivity to antiangiogenic-therapeutic regimens, might explain these differences. Except for wound infection, obesity has no significant impact on surgical procedures. The underlying mechanisms linking obesity to CRC are still a matter of debate, but metabolic syndrome, insulin resistance and modifications in levels of adipocytokines seem to be of great importance. Other biological factors such as the gut microbiota or bile acids are emerging. Many questions still remain unanswered: should preventive strategies specifically target obese patients? Is the risk of cancer great enough to propose prophylactic bariatric surgery in certain patients with obesity?
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) | 0.001 | 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