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
With the possible exception of radiation-induced leukemia, more is known about radiation-induced breast cancer than any other malignancy. Fourteen cohort studies have provided quantitative information on the level of risk following a wide range of doses in different populations around the world. Comprehensive studies have been conducted in Canada, Germany, Japan, Sweden and other Nordic countries, the United Kingdom, and the USA [Table I in text]. Key features are the linearity in the dose response (i.e., a straight line adequately fits the observed data), and the effect modification of age at exposure (i.e., risk is inversely related to exposure age and exposures past the menopausal ages appear to carry a very low risk); and the minimal effect of fractionating dose on subsequent risk. A recent combined analysis of almost 78,000 women and 1,500 breast cancer cases from eight cohorts confirmed the downturn in risk at the highest dose levels (related in part to the killing of cells rather than transformation) and that fractionation of dose has little influence on risk, at least on an absolute scale. It is not known whether persons predisposed to cancer are at enhanced risk of radiation-induced breast cancer from low-dose exposures, although this seems unlikely. New data on the effects of high doses following childhood exposures will be forthcoming from long-term studies of the survivors of childhood 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 | 0.001 | 0.001 |
| 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