A Review of the Animal and Human Trials of the Ad5-nCoV Vaccine Candidate
Bibliographic record
Abstract
Since the COVID-19 outbreak began, there has been an urgent need for a safe and effective vaccine to end this global pandemic. One such vaccine is the Ad5-nCoV, developed by CanSino Biologics Inc. This review aims to examine all animal and human trials conducted for this vaccine candidate. Search terms such as “Ad5-nCoV”, “recombinant adenovirus”, “COVID-19”, and “vaccine”, were used in varying combinations in the PubMed database to find published trial reports. It was concluded that Ad5-nCoV can induce a strong immune response in mice and ferret models and offer them protection against the inoculation of SARS-CoV-2. It also has a strong safety profile in human and can induce an adequate immune response in terms of RBD-specific antibodies and T cell responses, while neutralizing antibody response and seroconversion was mediocre. The publish trial reports support the further testing of this vaccine candidate and it is preparing to enter phase 3 clinical trials.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".