Bibliographic record
Abstract
Viral vectors have been frequently applied for vaccine development. It has also been the case for vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to tackle the coronavirus disease 2019 (COVID-19) pandemic. A multitude of different viral vectors have been mainly targeting the SARS-CoV-2 spike (S) protein as antigen. Intramuscular injection has been most commonly used, but also intranasal administration has been tested. Adenovirus vector-based vaccines are the most advanced with several vaccines receiving Emergency Use Authorization (EUA). The simian ChAdOx1 nCoV-19 vaccine applied as a prime-boost regimen has provided 62.1–90% vaccine efficacy in clinical trials. The Ad26.COV2.S vaccine requires only one immunization to provide protection against SARS-CoV-2. The rAd26-S/rAd5-S vaccine utilizes the Ad26 serotype for the prime immunization followed by a boost with the Ad5 serotype resulting in 91.2% vaccine efficacy. All adenovirus-based vaccines are used for mass vaccinations. Moreover, vaccine candidates based on vaccinia virus and lentivirus vectors have been subjected to clinical evaluation. Among self-replicating RNA viruses, vaccine vectors based on measles virus, rhabdoviruses, and alphaviruses have been engineered and tested in clinical trials. In addition to the intramuscular route of administration vaccine candidates based on influenza viruses and adenoviruses have been subjected to intranasal delivery showing antibody responses and protection against SARS-CoV-2 challenges in animal models. The detection of novel more transmissible and pathogenic SARS-CoV-2 variants added concerns about the vaccine efficacy and needs to be monitored. Moreover, the cause of recently documented rare cases of vaccine-induced immune thrombotic thrombocytopenia (VITT) must be investigated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".