Bibliographic record
Abstract
W hen individuals become infected with any virus, the first question often is, how sick will they get?The coronavirus disease 2019 (COVID-19) pandemic highlighted this notion for all of us.The greatest risk factor for hospitalization and death was quickly realized to be age, but as always, there were exceptions.There were cases of young vaccinated individuals getting very sick with COVID-19, and at the same time, most of us know of an elderly individual who experienced only mild symptoms, even before vaccines were available.Now that the urgency of the pandemic seems to have subsided, we finally have time to truly understand this virus and the disease it causes.One main focus going forward will be to figure out what else predicts disease severity, who is most at risk for severe disease, as well as which factors contribute to the development of long COVID-19.Many virus infections present with similar inflammatory profiles, and for many of these infections, we do not yet know what predicts disease severity.In this issue, Jose et al. have investigated the expression of indoleamine 2,3dioxygenase (IDO) 1 pathway genes in severe dengue patients.Using a principal component analysis, the authors examined the relationships between gene expression profiles and disease severity, as well as laboratory markers of clinical severity.Based on their findings, they concluded that profiling the baseline expression patterns of IDO pathway genes can aid in the identification of dengue patients most at risk for severe disease.Also on the topic of innate immunity, Zhang et al. examined Toll-like receptor 3 (TLR3) gene single nucleotide polymorphisms (SNPs) in 370 Kaposi's sarcoma-associated herpesvirus (KSHV; HHV8)-infected patients to look for effects on interferon (IFN)-c levels.The authors identified two TLR3 SNPs that showed protective effects against KSHV infection, and from this they concluded that genetic variants in TLR3 reduce the risk of KSHV infection and affect KSHV reactivation among HIV-infected individuals, especially in the Uyghur population.As already mentioned, the ability to predict disease severity in COVID-19 would be extremely valuable.In an article by Gabr et al., T lymphocyte subsets and NK cells
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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 | 0.031 | 0.086 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.023 | 0.042 |
| Insufficient payload (model declined to judge) | 0.006 | 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".