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
Considerable knowledge has been acquired about the determinants of female breast cancer. A positive family history among first-degree relatives is associated with an increased risk of breast cancer, as is a past history of benign proliferative breast disease. Risk increases with decreasing age at menarche, and with increasing age at first full term pregnancy and at menopause. Pregnancy is followed by a short-term increase in risk, followed by a long-term decrease. Risk increases with age. Evidence that environmental determinants are involved comes from the study of migrant populations: migrants assume the risk of breast cancer prevalent in their new environment, arguing against the hypothesis that risk is determined solely by genetic mechanisms. The best understood environmental determinant is ionizing radiation: it increases risk in a dose-dependent fashion. While ecologic studies of diet supported the hypothesis that high fat intake increases risk, cohort and case-control studies have yielded conflicting evidence, casting doubt on this hypothesis. However, weight gain during adult life is associated with an increased risk. Some drugs increase risk, specifically exogenous oestrogens and ethanol. The anti-oestrogen tamoxifen reduces risk. Recent evidence shows that both passive and active exposure to tobacco smoke is associated with an increased risk of breast cancer. Some women may be more susceptible to the effects of tobacco smoke on a genetic basis. Undoubtedly, other environmental determinants of breast cancer will be discovered.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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