In This Issue • Aging With HIV/AIDS
Bibliographic record
Abstract
After three decades of combating HIV/AIDS, scientists have made advances that have helped HIV-infected individuals live longer and better quality lives. These advances have also created new challenges as now over a quarter of the U.S. HIV-infected population is ages 50 and older. The Behavioral and Social Research Division at the National Institute on Aging (NIA) supports research on health and sexuality in the older population and on evaluating the cost-effectiveness of interventions. This work has contributed to understanding HIV/AIDS risk factors in older adults, the cost-effectiveness of HIV screening for older adults, and evaluation of the President’s Emergency Plan for AIDS Relief (PEPFAR) in Africa. This newsletter reviews some recent research, both NIA-sponsored and other research, on aging and HIV/AIDS. Aging With HIV/AIDS With the success of antiretroviral medications, longevity has increased for those with HIV and AIDS. In addition, improved screening methods identify more new cases of HIV/AIDS. As a result, the number of older adults living
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.110 | 0.045 |
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".