Detection of avian influenza virus in surface waters using passive samplers
Bibliographic record
Abstract
Avian influenza (AIV) remains a global concern not only for humans as a pandemic threat but pose a risk to poultry, wildlife, and livestock. The detection of AIV in the environment traditionally has relied on reactive surveillance, limiting proactive response. This study assessed the detection of Pan-influenza A virus (Pan-FluA) and hemagglutinin subtype H5 genes in surface water using novel passive samplers and molecular analyses. Pan-FluA RNA was detected at concentrations from 2.1 × 10 5 to 5.6 × 10 12 copies sampler −1 and H5 RNA at concentrations from 2.2 × 10 4 to 1.8 × 10 11 copies sampler −1 . Detections aligned with fall migration and waterfowl activity but also underscored the importance of monitoring interface zones influenced by wildlife, agriculture, and wastewater. Among other hemagglutinin subtypes detected, sequence analyses confirmed the presence of H5 lineages consistent with those reported for H5N1, H5N6, and H5N8. These findings ultimately demonstrate the potential of surface water surveillance as a scalable strategy for AIV detection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".