AMOR: A proposed cooperative effort to improve outcomes of childhood cancer in Central America
Bibliographic record
Abstract
The dramatic reduction of pediatric cancer mortality rates has been one of the greatest accomplishments of contemporary medicine. About 80% of children with cancer are now expected to be cured by current therapies. However, most of the world's children have no access to cancer treatment. The translation of effective pediatric cancer therapies to impoverished regions of the world presents an enormous challenge to the health care profession. Over the past 20 years, efforts have been under way to extend adequate cancer treatment to an increasing number of children in developing countries. These initiatives, collectively designated "twinning programs," consist essentially of a partnership between a pediatric cancer unit in a developing country and a group of health care providers in the developed world. Here we review the twinning programs that have been implemented in Central America, discuss their impact on the development of local resources and the outcome of childhood cancer, and propose a collaborative research initiative aimed at improving the international dissemination of progress in pediatric hematology-oncology.
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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 | 0.021 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".