Efficacy of chloramine-T as a treatment for amoebic gill disease (AGD) in marine Atlantic salmon (Salmo salar L.)
Bibliographic record
Abstract
Atlantic salmon with amoebic gill disease (AGD) were treated with chloramine-T to compare its effectiveness with that of freshwater bathing. In 250-L tank trials, treatment of seawater with chloramine-T reduced amoeba density on the gills to levels significantly lower than when treated with seawater alone. There was no further change in amoeba levels in fish bathed for 3 or 6 h compared with 1 h of treatment. Plasma lactate levels in fish bathed in chloramine-T for 6 h showed no differences across treatments. In 1000-L tank trials using freshwater alone or seawater with chloramine-T, significant reductions in amoeba density occurred compared with pre-bath levels. Histological analysis of gill tissue revealed AGD lesion levels to increase, then to return to pre-bath levels within 1 week for freshwater-treated fish, while chloramine-T- and seawater-treated fish had higher levels of AGD lesions from 2 weeks post bathing. Immunodot-blot data indicated an initial significant increase in prevalence of lesions in seawater and chloramine-T-treated fish, which declined to levels significantly lower than pre-bath levels by 3 weeks post bathing, compared with the freshwater-treated fish, which had significantly lower levels than controls by 2 weeks post bathing. At reducing amoeba density, it is apparent that bathing AGD-affected Atlantic salmon in seawater with chloramine-T proved at least as effective as freshwater.
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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 | 0.000 |
| 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".