Development of a <i>Piscirickettsia salmonis</i> immersion challenge model to investigate the comparative susceptibility of three salmon species
Bibliographic record
Abstract
Abstract Piscirickettsia salmonis, the aetiological agent of salmonid rickettsial septicaemia (SRS), is a global pathogen of wild and cultured marine salmonids. Here, we describe the development and application of a reproducible, standardized immersion challenge model to induce clinical SRS in juvenile pink (Oncorhynchus gorbuscha), Atlantic (Salmo salar) and sockeye salmon (O. nerka). Following a 1‐hr immersion in 105 colony‐forming units/ml, cumulative mortality in Atlantic salmon was 63.2% while mortality in sockeye salmon was 10%. Prevalence and levels of the bacterium in kidney prior to onset of mortality were lower in sockeye compared with Atlantic or pink salmon. The timing and magnitude of bacterial shedding were estimated from water samples collected during the exposure trials. Shedding was estimated to be 82‐fold higher in Atlantic salmon as compared to sockeye salmon and peaked in the Atlantic salmon trial at 36 d post‐immersion. These data suggest sockeye salmon are less susceptible to P. salmonis than Atlantic or pink salmon. Finally, skin lesions were observed on infected fish during all trials, often in the absence of detectable infection in kidney. As a result, we hypothesize that skin is the primary point of entry for P. salmonis during the immersion challenge.
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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 | 0.001 |
| 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".