Investigations on the role of the salmon louse, <i>Lepeophtheirus salmonis</i> (Caligidae), as a vector in the transmission of <i>Aeromonas salmonicida</i> subsp. <i>salmonicida</i>
Bibliographic record
Abstract
A bacteria-parasite challenge model was used to study the role of sea lice, Lepeophtheirus salmonis (Copepoda), as a vector of Aeromonas salmonicida subsp. salmonicida. Three hypotheses were tested: (i) L. salmonis can acquire A. salmonicida subsp. salmonicida via water bath exposure; (ii) L. salmonis can acquire the bacteria via parasitizing infected Atlantic salmon, Salmo salar; and (iii) L. salmonis can transmit the bacteria to naïve Atlantic salmon via parasitism. Adult L. salmonis exposed to varying A. salmonicida subsp. salmonicida suspensions (10(1) -10(7) cells mL(-1) ) for 1.0, 3.0 or 6.0 h acquired the bacteria externally (12.5-100%) and internally (10.0-100%), with higher prevalences associated with the highest concentrations and exposures. After exposure to 10(7) cells mL(-1) , viable A. salmonicida subsp. salmonicida could be isolated from the external carapace of L. salmonis for 120 h. Lepeophtheirus salmonis also acquired the bacteria externally and internally from parasitizing infected fish. Bacterial transmission was observed only when L. salmonis had acquired the pathogen internally via feeding on 'donor fish' and then by parasitizing smaller (<50 g) 'naive' fish. Under specific experimental conditions, L. salmonis can transfer A. salmonicida subsp. salmonicida via parasitism; however, its role as a mechanical or biological vector was not defined.
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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".