Improving the Youth HIV Prevention and Care Continuums: The Adolescent Medicine Trials Network for HIV/AIDS Interventions
Bibliographic record
Abstract
BACKGROUND: Epidemiologic and clinical information in the United States indicate that HIV transmission and acquisition among adolescents and young adults (youth) remain unchanged, without improvement. Interventions to prevent HIV transmission among youth are critically needed, as are interventions to improve adherence to all components of the continuum of care for youth living with HIV. OBJECTIVE: The primary mission of the Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN) is to conduct both independent and collaborative research that explores promising behavioral, microbicidal, prophylactic, therapeutic, and vaccine modalities in HIV-infected and at-risk youth aged between 12 and 24. METHODS: Through the ATN, the National Institutes of Health is supporting HIV interventional research for youth in the United States. RESULTS: The ATN comprises 3 cooperative multiproject research programs and a coordinating center. Each program is led by a network hub and has well-defined research themes to assist, guide, and coordinate HIV research project activities. CONCLUSIONS: ATN activities encompass the full spectrum of research needs for youth, from HIV primary prevention for at-risk youth in the community to secondary and tertiary prevention with clinical management of HIV infection among youth living with HIV experiencing adherence challenges.
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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 | 0.053 | 0.109 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.023 | 0.042 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".