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
More than a quarter of the world's \n population is between the ages of 10 and 24. Most (86 \n percent) of the world's 1.7 billion young people live \n in developing countries, where they are often 30 percent or \n more of the population. At first glance, youth appears to be \n a relatively healthy although not hazard-free period of \n life. Young people account for 15 percent of the disease and \n injury burden worldwide and over one million die each year, \n mainly from preventable causes. Nonetheless, roughly 70 \n percent of premature deaths among adults can be linked to \n behavior initiated during adolescence, such as tobacco use, \n poor eating habits, and risky sex. Investing in health and \n development of young people is not only the right thing to \n do, it's the smart thing for countries that want their \n economies to grow faster: 1) reducing HIV infection in young \n people will reduce the devastating economic impact of \n HIV/AIDS; 2) when young people postpone marriage and \n childbearing, family size falls and population growth slows. \n Combined with investments in health and education, these \n changes contribute to higher economic growth and incomes; \n and 3) investments to head off negative behaviors such as \n tobacco use and drug abuse will pay off later for \n individuals and for society.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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