The African Organization for Research and Training in Cancer: Historical Perspective
Bibliographic record
Abstract
The African Organization for Research and Training in Cancer (aortic) is a bilingual (English and French) nonprofit organization dedicated to the promotion of cancer control and palliation in Africa. Its mission in respect to cancer control in Africa includes support of research and training;provision of relevant and accurate information on the prevention, early diagnosis, treatment, and palliation of cancer;promotion of public awareness about cancer and reduction of the stigma associated with it.In seeking to achieve its goal of cancer control in Africa, aortic strives to unite the continent and to make a positive impact throughout the region by collaboration with health ministries and global cancer organizations. The organization's key objectives are to further research relating to cancers prevalent in Africa, to support training programs in oncology for health care workers, to deal with the challenges of creating cancer control and prevention programs, and to raise public awareness of cancer in Africa. It also plans to organize symposia, workshops, meetings, and conferences that support its mission.Founded in September 1982, aortic was active only between 1983 (when its inaugural conference was held in the City of Lome, Togo, West Africa) and the late 1980s. The organization subsequently became inactive and moribund. In 2000, a group of expatriate African physicians and scientists joined in an effort with their non-African friends and colleagues to reactivate the dormant organization. Since its reactivation, aortic has succeeded in putting cancer on the public health agenda in many African countries by highlighting Africa's urgent need for cancer control and by holding meetings every two years in various African cities. National and international cancer control organizations worldwide have recognized the challenges facing Africa and have joined in aortic's mission.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".