A Pediatric Infectious Diseases Perspective of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Novel Coronavirus Disease 2019 (COVID-19) in Children
Bibliographic record
Abstract
Understanding the role that children play in the clinical burden and propagation of severe acute respiratory syndrome coronavirus 2, responsible for coronavirus disease 2019 (COVID-19) infections, is emerging. While the severe manifestations and acute clinical burden of COVID-19 have largely spared children compared with adults, understanding the epidemiology, clinical presentation, diagnostics, management, and prevention opportunities and the social and behavioral impacts on child health is vital. Foremost is clarifying the contribution of asymptomatic and mild infections to transmission within the household and community and the clinical and epidemiologic significance of uncommon severe post-infectious complications. Here, we summarize the current knowledge, identify resources, and outline research opportunities. Pediatric infectious diseases clinicians have a unique opportunity to advocate for the inclusion of children in epidemiological, clinical, treatment, and prevention studies to optimize their care as well as to represent children in the development of guidance and policy during pandemic response.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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; 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".