Comparative bacterial genomics and fish vaccinology: genomic and phenotypic analysis of Vibrio anguillarum isolated from lumpfish (Cyclopterus lumpus) and vaccine evaluation in sablefish (Anoplopoma fimbria) against Aeromonas salmonicida
Bibliographic record
Abstract
Although aquaculture is the fastest growing food-producing industry in the world, it is negatively impacted by parasites and infectious diseases. Bacterial infections are the most important diseases of emergent Canadian aquaculture species such as lumpfish (Cyclopterus lumpus) and sablefish (Anoplopoma fimbria). Aeromonas salmonicida and Vibrio anguillarum, both Gram-negative pathogens, are the most prevalent infectious diseases agents affecting lumpfish aquaculture in the North Atlantic, meanwhile A. salmonicida is the most common pathogen in the sablefish aquaculture industry in the Pacific coast. Comparative genomic analysis of V. anguillarum and A. salmonicida isolates from lumpfish and sablefish outbreaks, respectively, can provide insights into bacterial evolution and virulence, and contribute to effective vaccine design programs. Currently, there are no commercial vaccines available specifically for lumpfish against V. anguillarum, and for sablefish against A. salmonicida. Therefore, the objectives of this study were to: i) analyze the genome and phenotype of V. anguillarum strain J360 isolated from infected lumpfish (Chapter 2); and ii) develop an infection model for atypical A. salmonicida strain J410 in sablefish to evaluate commercial vaccines and an autogenous vaccine (Chapter 3).
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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 | 0.001 |
| 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".