Editorial: Exosomes, miRNAs, and lncRNAs in breast cancer: Therapeutic and diagnostic applications
Bibliographic record
Abstract
Breast cancer is a complex disease that can be influenced by a variety of factors, including genetics, lifestyle, and environmental factors. It is classified into different subtypes based on the presence or absence of hormone receptors and HER2 expression, as well as the signature profile of the gene of the tumor cells. The presence of estrogen and progesterone receptors, which are proteins that respond to female hormones, is a paramount factor not only in breast cancer development but also treatment.Tumors that express these receptors are referred to as ER-positive or PRpositive, and can often be treated with hormone therapy. HER2 is another protein that plays a role in the growth and division of cells, and tumors that overexpress HER2 are referred to as HER2-positive. In addition to these receptor-based subtypes, breast cancer can also be classified based on gene expression profiles, which can provide insight into the underlying biology of the tumor and help guide treatment decisions. Some common gene expression subtypes include HER2-enriched, luminal A, and B type, and triple-negative (when ER, PR, and HER2 are absent) breast cancer.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".