Within-farm spread of infectious salmon anemia virus (ISAV) in Atlantic salmon Salmo salar farms in Chile
Bibliographic record
Abstract
Spread of infectious salmon anemia virus (ISAV) at the cage level was quantified using a subset of data from 23 Atlantic salmon Salmo salar farms located in southern Chile. Data collected from official surveillance activities were systematically organized to obtain detailed information on infectious salmon anemia (ISA) outbreaks. Descriptive statistics for outbreak duration, proportion of infected fish, and time to secondary infection were calculated to quantify the magnitude of ISAV incursions. Linear and multiple failure time (MFT) regression models were used to determine factors associated with the cage-level reproduction number (Rc) and hazard rate (HR) for recurrent events, respectively. In addition, the Knox test was used to assess if cage-to-cage transmissions were clustered in space and time. Findings suggest that within farms, ISA outbreaks, on average, lasted 30 wk (median = 26 wk, 95% CI = 24 to 37 wk) and affected 57.3% (95% CI = 47.7 to 67.0%) of susceptible cages. The median time to secondarily diagnosed cages was 23 d. Occurrence of clinical ISAV outbreaks was significantly associated with increased Rc, whereas increased HR was significantly associated with clinical outbreaks and with a large number of fish. Spatio-temporal analysis failed to identify clustering of cage cases, suggesting that within-farm ISAV spread is independent of the spatial location of the cages. Results presented here will help to better understand ISAV transmission, to improve the design of surveillance programs in Chile and other regions in which salmon are intensively farmed, and to examine the economic impact of ISAV and related management strategies on various cost and demand shifting factors.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".