A Gene Signature for Predicting Outcome in Patients with Basal-like 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
Basal-like breast cancer is a molecular subtype of breast cancer with a poor prognosis. Follow-up studies of long-term outcome in these patients, demonstrates they can be separated into two clinical groups: those who succumb to their disease within the first 5 years and those expected to show excellent long term survival. Currently available clinical/histopathological variables as well as molecular signatures show little capacity to identify basal breast cancer patients with either a high or low risk of disease relapse. Using data derived from 85 basal-like breast cancer patients, we identified a 14-gene signature, which we subsequently validated on an additional 49 basal breast cancer patient set. The ability to distinguish between these two sub-groups of basal breast cancer patients at the time of initial diagnosis would permit tailoring aggressive therapeutic regimens to those patients with a poor prognosis and conversely avoid such therapy in low risk patients.
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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