Estimation of Parameters Influencing Waterborne Transmission of Infectious Hematopoietic Necrosis Virus (IHNV) in Atlantic Salmon (Salmo salar)
Bibliographic record
Abstract
Understanding how pathogenic organisms spread in the environment is crucial for the management of disease, yet knowledge of propagule dispersal and transmission in aquatic environments is limited. We conducted empirical studies using the aquatic virus, infectious hematopoietic necrosis virus (IHNV), to quantify infectious dose, shedding capacity, and virus destruction rates in order to better understand the transmission of IHN virus among Atlantic salmon marine net-pen aquaculture. Transmission of virus and subsequent mortality in Atlantic salmon post-smolts was initiated with as low as 10 plaque forming units (pfu) ml(-1). Virus shedding from IHNV infected Atlantic salmon was detected before the onset of visible signs of disease with peak shed rates averaging 3.2 × 10(7) pfu fish(-1) hour(-1) one to two days prior to mortality. Once shed into the marine environment, the abundance of free IHNV is modulated by sunlight (UV A and B) and the growth of natural biota present in the seawater. Virus decayed very slowly in sterilized seawater while rates as high as k = 4.37 d(-1) were observed in natural seawater. Decay rates were further accelerated when exposed to sunlight with virus infectivity reduced by six orders of magnitude within 3 hours of full sunlight exposure. Coupling the IHNV transmission parameter estimates determined here with physical water circulation models, will increase the understanding of IHNV dispersal and provide accurate geospatial predictions of risk for IHNV transmission from marine salmon sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".