Investigating the relationship between mammographic breast density and triple negative breast cancer in Nova Scotia, Canada
Bibliographic record
Abstract
The study objectives were to estimate the association between mammographic breast density (MBD) and triple negative breast cancers (TNBC); as well as to estimate the discriminatory ability of MBD, alone and with clinical risk factors, in the screening population. This case-control study consisted of 121 TNBC cases with a full-field digital mammography (FFDM) screen in 2009-2015 in Nova Scotia. The 6807 controls were women with a prior negative FFDM screening mammogram episode. Odds ratios and areas under curves were reported for models generated using two measures of MBD, percent and BI-RADS categories (5th ed.), both separately and in combination. Aside from the two forms of MBD, other variables included self-reported risk factors (menopausal status, hormone replacement therapy use, parity, family history), biopsy history, and derived breast volume. A significant positive association was found between MBD and TNBC in this screening population. The addition of clinical factors to density improved the discriminatory ability of the prediction models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".