Characterization of Specific Humoral Immunity in Asymptomatic SARS-CoV-2 Infection
Bibliographic record
Abstract
Abstract The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in December 2019 caused a huge blow to both global public health and global economy. At the early stage of the coronavirus disease 2019 (COVID-19) epidemic, asymptomatic individuals with SARS-CoV-2 infection were ignored, without appropriate identification and isolation. However, asymptomatic individuals proved to comprise a high proportion of all SARS-CoV-2-infected individuals, which greatly contributed to the rapid and wide spread of this disease. In this review, we summarize the latest advances in epidemiological characteristics, diagnostic assessment methods, factors related to the establishment of SARS-CoV-2 asymptomatic infection, as well as humoral immune features after SARS-CoV-2 infection or vaccination in asymptomatic individuals, which would contribute to effective control of ongoing COVID-19 epidemic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".