Data from: Immune response genes and pathogen presence predict migration survival in wild salmon smolts
Bibliographic record
Abstract
AbstractWe present the first data to link physiological responses and pathogen presence with subsequent fate during migration of wild salmonid smolts. We tagged and non-lethally sampled gill tissue from sockeye salmon (Oncorhynchus nerka) smolts as they left their nursery lake (Chilko Lake, BC, Canada) to compare gene expression profiles and freshwater pathogen loads with migration success over the first ~1150 km of their migration to the North Pacific Ocean using acoustic telemetry. Fifteen percent of smolts were never detected again after release and these fish had gene expression profiles consistent with an immune response to one or more viral pathogens compared with fish that survived their freshwater migration. Among the significantly up-regulated genes of the fish that were never detected post-release were MX (Interferon-induced GTP-binding Protein Mx) and STAT1 (Signal transducer and activator of transcription 1-alpha/beta), which are characteristic of a type I interferon response to viral pathogens. The most commonly detected pathogen in the smolts leaving the nursery lake was infectious hematopoietic necrosis virus (IHNV). Collectively, these data show that some of the fish assumed to have died after leaving the nursery lake appeared to be responding to one or more viral pathogens and had elevated stress levels that could have contributed to some of the mortality shortly after release. We present the first evidence that changes in gene expression may be predictive of some of the fresh water migration mortality in wild salmonid smolts.
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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) | 0.002 | 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".