Aquaculture fouling: Efficacy of potassium monopersulphonate triple salt based disinfectant (Virkon® Aquatic) against<i>Ciona intestinalis</i>
Bibliographic record
Abstract
With the increasing spread of invasive marine species and their detrimental effects on aquaculture operations globally, mitigation strategies need to be optimized to mitigate economic impacts. The efficacy of a potassium monopersulphonate triple salt based disinfectant used in the aquaculture industry (Virkon® Aquatic at 0.5-5%) was evaluated against the solitary tunicate Ciona intestinalis, as well as the susceptibility of three different age groups of C. intestinalis to the treatment and the effect of the disinfectant on mussel mortality. Younger C. intestinalis were most affected by all treatments, and almost all immersion applications significantly decreased the biomass of C. intestinalis compared to untreated plates. Disinfectant solutions of ≥ 1% reduced biomass below pre-treatment levels. Mussel mortality was low, especially for solutions <3%. C. intestinalis should be treated 4 weeks post-settlement to maximize antifouling treatment effects. Immersion in 3% disinfectant for 30 s reduced the biomass of C. intestinalis by up to 89% and would be feasible in field applications using existing treatment equipment.
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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) | 0.001 | 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".