Global transcriptional analysis of short-term hepatic stress responses in Atlantic salmon (Salmo salar) exposed to depleted uranium
Bibliographic record
Abstract
Potential environmental hazards of radionuclides are often studied at the individual level. Sufficient toxicogenomics data at the molecular/cellular level for understanding the effects and modes of toxic action (MoAs) of radionuclide is still lacking. The current article introduces transcriptomic data generated from a recent ecotoxicological study, with the aims to characterize the MoAs of a metallic radionuclide, deplete uranium (DU) in an ecologically and commercially important fish species, Atlantic salmon (Salmo salar). Salmon were exposed to three concentrations (0.25, 0.5 and 1.0 mg/L) of DU for 48 h. Short-term global transcriptional responses were studied using Agilent custom-designed high density 60,000-feature (60 k) salmonid oligonucleotide microarrays (oligoarray). The microarray datasets deposited at Gene Expression Omnibus (GEO ID: GSE58824) were associated with a recently published study by Song et al. (2014) in BMC Genomics. The authors describe the experimental data herein to build a platform for better understanding the toxic mechanisms and ecological hazard of radionuclides such as DU in fish.
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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".