Bibliographic record
Abstract
Vaccinations are an important means of controlling communicable diseases, especially in developing countries where patients do not have regular access to adequate healthcare. However, barriers such as cost and lack of resources are particularly problematic in the developing world and limit the adoption of vaccines. Meanwhile, in developed nations, the fear of injections contributes to the growing problem of vaccine avoidance and hesitancy. To address these barriers, a microneedle patch vaccine was recently created by Dr Prausnitz and his research team at the Georgia Institute of Technology in Atlanta, in which application of the patch to the skin allows polymer microneedles containing the vaccine to puncture the epidermis, dissolve, and elicit an immunogenic response. Research using rodent and primate models have demonstrated this technology’s effectiveness, and a human clinical trial using an influenza microneedle patch vaccine is currently being conducted. Future trials are being planned for microneedle patch vaccines against measles and polio as well. This technology’s nearly pain-free administration, portability, and relative ease of delivery can help address patients’ apprehensions to hypodermic needles and lessen administration costs and efforts. While the microneedle patch vaccine is a promising vaccination modality that can potentially be used to overcome the barriers to vaccination, further studies will need to be conducted to determine adverse events. Also, strategies for patient education and potential legal issues will need to be addressed before widespread use of this novel vaccination modality.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".