What Do We Mean When We Ask for More Metastatic Breast Cancer Research?
Bibliographic record
Abstract
Background: Almost all deaths from breast cancer are due to metastasis. People living with metastatic breast cancer (MBC) and their loved ones have been concerned about the lack of research progress. The purposes of this paper were to analyze breast cancer research spending in Canada, and to evaluate whether MBC research was aligned with patient priorities. The results from the MBC Priority Setting Partnership (MBC PSP) were used as an approximation of patient priorities. Methods: The data source was the Canadian Cancer Research Survey. MBC projects were identified and mapped to the patient priorities.Results: This analysis found that 18% of breast cancer research investment was directed to MBC, with a large proportion of this research investment focused on the biology of metastasis. Four of the top 10 MBC PSP priorities had not been addressed: optimal sequence of therapy, role of continuous versus intermittent treatment, benefits of early palliative care, and best methods for patient education. Conclusion: These figures provide a baseline from which any increases in MBC research and improved alignment to patient priorities can be measured. A cooperative effort by funders, researchers, patients, caregivers, and health care providers is needed to address research gaps.
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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 | 0.034 | 0.147 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".