COVID‐19: Current knowledge in clinical features, immunological responses, and vaccine development
Bibliographic record
Abstract
The COVID-19 pandemic has unfolded to be the most challenging global health crisis in a century. In 11 months since its first emergence, according to WHO, the causative infectious agent SARS-CoV-2 has infected more than 100 million people and claimed more than 2.15 million lives worldwide. Moreover, the world has raced to understand the virus and natural immunity and to develop vaccines. Thus, within a short 11 months a number of highly promising COVID-19 vaccines were developed at an unprecedented speed and are now being deployed via emergency use authorization for immunization. Although a considerable number of review contributions are being published, all of them attempt to capture only a specific aspect of COVID-19 or its therapeutic approaches based on ever-expanding information. Here, we provide a comprehensive overview to conceptually thread together the latest information on global epidemiology and mitigation strategies, clinical features, viral pathogenesis and immune responses, and the current state of vaccine 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".