PRE-EXPOSING CANADA GEESE (<i>BRANTA CANADENSIS</i>) TO A LOW-PATHOGENIC H1N1 AVIAN INFLUENZA VIRUS PROTECTS THEM AGAINST H5N1 HPAI VIRUS CHALLENGE
Bibliographic record
Abstract
In previous studies we examined the role of Canada Geese (Branta canadensis) in the epidemiology of Eurasian highly pathogenic avian influenza (HPAI) H5N1. To expand on this and better understand how pre-exposure to heterosubtypic low-pathogenic avian influenza (LPAI) viruses might influence the outcome of H5N1 HPAI infection, we pre-exposed naïve juvenile Canada Geese to different North American wild-bird-origin LPAI viruses. We selected H1, H2, and H6 hemagglutinin subtype viruses based on their higher-order evolutionary relatedness to the H5 hemagglutinin. Pre-exposing Canada Geese to either H2N3 or H6N5 viruses did not protect them against a lethal H5N1 HPAI virus challenge. In addition, H5N1 was transmitted to naïve control birds that were placed among both groups resulting in death by 5 days postcontact. In contrast, Canada Geese that were pre-exposed to H1N1 were protected against a lethal H5N1 challenge, shed minimal amounts of the virus into the environment, and did not transmit the infection to naïve contact birds. None of the H1N1, H2N3, or H6N5 pre-exposure sera neutralized H5N1 in vitro; however, sera from H1N1-infected birds reduced virus plaque size but not number when compared with H2N3, H6N5, or negative sera, suggesting that antibodies directed against the neuraminidase may have had a role in the protective effects observed.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".