SAR-CoV-2 infection, emerging new variants and the role of activation induced cytidine deaminase (AID) in lasting immunity
Bibliographic record
Abstract
As the world faces a fourth COVID-19 spike, scientists are learning a lot more about the new SARS-CoV-2 strains that were previously unknown. Currently, the Delta versions of SARS-CoV-2 have become the prevalent strains in much of the world since it first appeared in India in late 2020. Researchers believe they have discovered why Delta has been so successful: those infected with it create significantly more virus than those infected with the original strain of SARS-CoV-2, making it extremely contagious. This has redirected the focus to how our immune system defends us from these various pathogens and initiates such varied responses. Hundreds of research papers have been published on the origins of long-lasting immune responses and disparities in the numbers of different immune cell types in COVID 19 survivors, but the primary architect of these discrepancies has yet to be discovered. In this essay, we will concentrate on the primary architect protein, activation induced cytidine deaminase (AID), which triggers molecular processes that allow our immune system to produce powerful antibodies and SARS-CoV-2 specific B cells, allowing us to outwit the virus. We believe that if we ever achieve permanent immunity to SARS-CoV-2 infection, AID will be the key to releasing it.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".