Molecular Diagnostic Assays for Detection of Viral Respiratory Pathogens in Institutional Outbreaks
Bibliographic record
Abstract
Outbreaks of viral respiratory disease in institutions may be associated with high morbidity and mortality, depending upon the viral etiology and the age and immune status of the affected patients. Control of outbreaks may include isolation and/or cohorting, and prophylaxis or treatment with specific antiviral agents may be indicated, all dependent upon the specific cause of the outbreak. Conventional methods of viral diagnosis detect only a limited number of the viruses that are known to cause outbreaks. The availability of sensitive and specific molecular assays has facilitated rapid diagnosis of a wider range of viruses from respiratory outbreaks. Molecular methods have distinct advantages over conventional methods, including the ability to rapidly develop assays for emerging viruses and new variants of existing viruses. In addition, molecular testing allows rapid detection of resistance to antiviral agents or mutations leading to increased virulence. However, high-throughput molecular testing requires batch processes that may compromise the ability to respond quickly to urgent testing demands.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".