P15-22. Potential synergies between HIV vaccines, microbicides and pre-exposure prophylaxis
Bibliographic record
Abstract
The Canadian HIV Vaccine Initiative (CHVI) is a five-year initiative between the Government of Canada and the Bill & Melinda Gates Foundation, and represents a significant Canadian contribution to the Global HIV Vaccine Enterprise. The CHVI is part of Canada's long-term and comprehensive approach to addressing HIV/AIDS at home and abroad, including the development of new prevention technologies (NPTs). In support of this, the CHVI explored the close relationship between HIV vaccines, microbicides and pre-exposure prophylaxis (PrEP). A discussion paper was commissioned to identify potential linkages and opportunities for collaborative efforts among the three NPTs in the context of the CHVI's four program areas: discovery and social research; clinical trial capacity building and networks; pilot-scale manufacturing facility for clinical trial lots; policy and regulatory issues, and; community and social dimensions. Information was gathered through document review of academic and grey literature. There are many common issues/challenges to advancing the development of new NPTs and significant opportunities for collaborative efforts among these NPT fields, including sustainability of funding and clinical trial capacity. The report also noted the importance of positioning HIV vaccines as part of an overall prevention strategy, and that taking advantage of synergies between NPTs could provide the best opportunity to advance the NPT development agenda. It is not known which technology will be available first or the timelines for availability. However, it is increasingly recognized by Canadian and global HIV stakeholders that NPTs need to be part of a comprehensive HIV prevention agenda to increase the chances of successfully responding to the HIV/AIDS epidemic in the future. Canada has recognized the importance of including NPTs in a broad HIV prevention framework currently in development.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.007 |
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".