Bibliographic record
Abstract
The immense burden of HIV disease in sub-Saharan Africa has focused international interest on HIV care, especially on the lack of access to antiretroviral therapy (ART). Difficulties in implementing ART in Africa include drug costs, adequate long-term funding sources, assurance of drug quality, and rapid development of the human resources and healthcare infrastructure needed to deliver ART. Important questions requiring study are the minimum level of laboratory monitoring and clinical support consistent with good treatment outcomes, the impact of antiretroviral drug resistance on treated individuals and communities, and the effect of ART on transmission at a community level. There are some concerns and risks. First, a focus on treatment could compromise the commitment of individuals to risk-reduction, and of governments to prevention. Second, health equity could be reduced, by diverting scarce public funds from basic care for the poorest, to costly disease-suppressive care for a small and probably elite group. In conclusion, while prevention must be the first priority, care is also essential. The vast prevailing economic inequity between the world's rich and poor is the fundamental determinant of inequities in health and healthcare, including care for HIV. The global community of healthcare workers must focus its substantial influence on changing political and economic policies that foster injustice and AIDS.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".