The impact of trained immunity in respiratory viral infections
Bibliographic record
Abstract
Epidemic peaks of respiratory viruses that co-circulate during the winter-spring seasons can be synchronous or asynchronous. The occurrence of temporal patterns in epidemics caused by some respiratory viruses suggests that they could negatively interact with each other. These negative interactions may result from a programme of innate immune memory, known as trained immunity, which may confer broad protective effects against respiratory viruses. It is suggested that stimulation of innate immune cells by a vaccine or a pathogen could induce their long-term functional reprogramming through an interplay between metabolic and epigenetic changes, which influence the transcriptional response to a secondary challenge. During the coronavirus disease 2019 pandemic, the circulation of most respiratory viruses was prevented by non-pharmacological interventions and then resumed at unusual periods once sanitary measures were lifted. With time, respiratory viruses should find again their own ecological niches. This transition period provides an opportunity to study the interactions between respiratory viruses at the population level.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".