Cross-sectional Study of the Health of Farmed Atlantic Salmon in British Columbia
Bibliographic record
Abstract
Currently, extensive information is collected by the Canadian federal government about fish that die on BC salmon farms (~10% of farmed salmon over the course of a year). In contrast, little information is publicly available about disease among fish that do not die on the farms (~90% of farmed salmon over the course of a year). The overall objective of our study is to determine if surveillance programs focusing on moribund and dead farmed fish are missing data important to wild salmon health by not sampling farm fish that are not moribund or dead. From 2013 to 2015, as part of the Strategic Salmon Health Initiative (SSHI), Fisheries and Oceans Canada (DFO) co-sponsored a detailed study of disease on four BC Atlantic salmon farms that involved regular sampling of live, moribund, and recently deceased fish. Some histopathology from one of these farms has been published (Di Cicco et al. 2017), and the SSHI team is preparing additional publications reporting specific findings from this work, but histopathology of large numbers of fish from the other three farms is not planned, outside of our proposed study.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".