Network analysis of farmed Atlantic salmon movements in British Columbia, Canada
Bibliographic record
Abstract
An inherent issue to the Atlantic salmon aquaculture production is the possible transmission of infectious pathogens due to the transportation of live fish. This study employed network analysis to model the contribution of Atlantic salmon transfers to the spread of pathogens. We used a publicly available salmon transfer dataset covering the period 2015-2022. Official records showed that 812 transfers of Atlantic salmon occurred between various British Columbian (BC) salmon production units in that timeframe. For the purpose of evaluating changes in the network structure of farmed Atlantic salmon movements, the daily networks were aggregated into two-year periods to generate a time-ordered series of biennial movements. The freshwater hatchery and marine netpen sites comprised the two types of facilities that made up the Atlantic salmon transfer network, which consisted of 99 nodes (facilities) and 350 edges (links) overall. All the networks showed both scale-free and small-world topology, which would encourage the persistence and spread of pathogens in the Atlantic salmon facilities while simultaneously making it easier to develop risk-based surveillance techniques by focusing on high centrality nodes. Additionally, the rare occurrence of high betweenness and reach, presence of disassortative mixing, negative correlation between the in- and out-degree and between ingoing and outgoing infection chain of facilities, and the identification of freshwater hatcheries as potential superspreaders all suggest that Atlantic salmon transfers might not play a significant role in the spread of pathogens between facilities in the British Columbian Atlantic salmon farming industry. Community detection revealed two or three communities persistently in the aquaculture management unit (AMU) level network, and it would be more effective to make zoning based on AMU. In conclusion, targeted surveillance efforts on high-centrality facilities can be employed to combat any infectious outbreak in the BC Atlantic salmon industry caused by live Atlantic salmon movement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.004 |
| 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) | 0.000 | 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 teacher head, 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".