Help is on the way: critical roles of CD4<sup>+</sup> T cells in infection and vaccination
Bibliographic record
Abstract
The July 2023 issue contains a Special Feature about CD4+ T cells in infection and vaccination. CD4+ T helper cells are composed of many specialized subsets that play critical roles in immune memory. These cells have been somewhat overshadowed in the infectious disease and vaccination literature by their CD8+ counterparts and B cells/antibodies, which have been easier to study with available techniques. Therefore, we designed this issue to shine a light on some of the latest knowledge on how CD4+ T cells contribute to protective immunity. This Special Feature includes both original research and review articles on techniques to study CD4+ T-cell subsets and their roles in influenza A virus or human papilloma virus infection, sepsis and following vaccination to severe acute respiratory syndrome coronavirus 2. This collection highlights how new techniques are enabling rapid knowledge gain on how these cells underpin key aspects of the generation of effective immune responses, information that will be essential for the treatment and prevention of infectious diseases.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".