State of Cancer Control in Rwanda: Past, Present, and Future Opportunities
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
Rwanda is a densely populated low-income country in East Africa. Previously considered a failed state after the genocide against the Tutsi in 1994, Rwanda has seen remarkable growth over the past 2 decades. Health care in Rwanda is predominantly delivered through public hospitals and is emerging in the private sector. More than 80% of patients are covered by community-based health insurance (Mutuelle de Santé). The cancer unit at the Rwanda Biomedical Center (a branch of the Ministry of Health) is responsible for setting and implementing cancer care policy. Rwanda has made progress with human papillomavirus (HPV) and hepatitis B vaccination. Recently, the cancer unit at the Rwanda Biomedical Center launched the country's 5-year National Cancer Control Plan. Over the past decade, patients with cancer have been able to receive chemotherapy at Butaro Cancer Center, and recently, the Rwanda Cancer Center was launched with 2 linear accelerator radiotherapy machines, which greatly reduced the number of referrals for treatment abroad. Palliative care services are increasing in Rwanda. A cancer registry has now been strengthened, and more clinicians are becoming active in cancer research. Despite these advances, there is still substantial work to be done and there are many outstanding challenges, including the need to build capacity in cancer awareness among the general population (and shift toward earlier diagnosis), cancer care workforce (more in-country training programs are needed), and research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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