Association between Transillumination Breast Spectroscopy and Quantitative Mammographic Features of the Breast
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
Transillumination breast spectroscopy (TiBS) uses nonionizing optical radiation to gain information about tissue properties directly from the breast. TiBS measurements were obtained from 225 women with normal mammograms. Principal component analysis was used to reduce the spectral data set into four principal components and to generate four TiBS scores (t1-t4) for each woman. These components and scores represent light scattering, water, lipid, and hemoglobin content. Percent density, dense area, and nondense area were measured using Cumulus. The association between TiBS scores and quantitative mammographic features was analyzed using linear regression stratified by menopausal status and adjusted for body mass index. Among premenopausal women, t1 and t3 were significantly associated with percent density (beta t1 = -0.14, P = 0.04; beta t3 = -2.43, P < 0.0001), whereas t2 and t3 were significantly associated with dense area (beta t2 = -1.57, P < 0.0001; beta t3 = -2.54, P < 0.0001). Among postmenopausal women, t1, t3, and t4 were significantly associated with percent density (beta t1 = -0.30, P < 0.0001; beta t3 = -2.51, P < 0.0001; beta t4 = 4.75, P < 0.0001) and dense area (beta t1 = -0.19, P = 0.004; beta t3 = -2.13, P = 0.002; beta t4 = 5.02, P < 0.0001). Scores t2 and t4 were also significantly correlated with age among postmenopausal women (rt2 = 0.41 and rt4 = -0.36). Given the association with quantitative mammographic features and tissue changes related to age and menopause, TiBS scores may prove useful as intermediate markers in studies of breast cancer etiology and prevention.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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