The Association of Measured Breast Tissue Characteristics with Mammographic Density and Other Risk Factors for Breast Cancer
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
BACKGROUND: We have examined the relationships between the measured properties of breast tissue and mammographic density and other risk factors for breast cancer, using breast tissue obtained at forensic autopsy and not selected for the presence of abnormalities. METHODS: We used randomly selected tissue blocks taken from breast tissue slices obtained by s.c. mastectomy at the time of forensic autopsy to measure histologic features using quantitative microscopy. The proportions of the biopsy occupied by cells (estimated by nuclear area), glandular structures, and collagen were determined. These measurements were examined in relation to the percent density in the faxitron image of the tissue slice from which the biopsy was taken and other risk factors for breast cancer. RESULTS: The percent mammographic density was associated with the proportion of the area of the biopsy occupied by nuclei, both epithelial and nonepithelial, and by collagen and the area of glandular structures. Several other risk factors for breast cancer, notably body weight, parity, and number of births, and menopausal status, that are associated with variations in mammographic density, were also associated with differences in one or more of these tissue features. CONCLUSION: All risk factors for breast cancer must ultimately exert their influence by an effect on the breast, and these findings suggest that, for some risk factors, this influence includes an effect on the number of cells and the quantity of collagen.
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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 | 0.000 |
| 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) | 0.000 | 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