Priorities for sexually transmitted infection vaccine research and development: Results from a survey of global leaders and representatives
Bibliographic record
Abstract
OBJECTIVE: To determine the sexually transmitted infection (STI) vaccine research priorities of global leaders in STI vaccine research, development, and service provision. METHODS: symposium preceding the STI & HIV World Congress in 2019 were invited to complete an electronic survey. We asked participants to rank items by importance/priority for STI vaccine development for the following areas of focus: specific STIs (gonorrhea, chlamydia, syphilis, herpes, and trichomoniasis), broad research domains (basic science, funding, communication, program planning, and vaccine hesitancy), and specific research activities related to these domains. We calculated weighted value scores based on the ranking (e.g., first, second, third) and the total number of responses in order to produce a ranked list of the priorities. RESULTS: A total of 46 out of 97 (44%) symposium attendees responded to the survey. Gonorrhea was identified as the STI that should be prioritized for vaccine development, followed by syphilis with weighted value scores of 3.82 and 3.37, respectively, out of a maximum of five. Basic science (and vaccine development) was the domain ranked with the highest priority with a weighted value score of 4.78 out of six. Research activities related to basic science and vaccine development (including pre-clinical and clinical trials, and surveillance measures) and increased funding opportunities were the most highly ranked activities in the "STI vaccine development" and "research domains and activities" categories. CONCLUSION: symposium prioritized continued scientific work in vaccine development and program planning. Gonorrhea was identified as the highest priority infection, followed by syphilis.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".