Clustering pattern and evolution characteristic of microRNAs in grass carp (Ctenopharyngodon idella)
Bibliographic record
Abstract
BACKGROUND: A considerable fraction of microRNAs (miRNAs) are highly conserved, and certain miRNAs correspond to genomic clusters. The clustering of miRNAs can be advantageous, possibly by allowing coordinated expression. However, little is known about the evolutionary forces responsible for the loss and acquisition of miRNA and miRNA clusters. RESULTS: The results demonstrated that several novel miRNAs arose throughout grass carp evolution. Duplication and de novo production were critical strategies for miRNA cluster formation. Duplicates accounted for a smaller fraction of the expansion in the grass carp miRNA than de novo creation. Clustered miRNAs are more conserved and change slower, whereas unique miRNAs usually have high evolution rates and low expression levels. The expression level of miRNA expression in clusters is strongly correlated. CONCLUSIONS: This study examines the genomic distribution, evolutionary background, and expression regulation of grass carp miRNAs. Our findings provide novel insights into the genesis and development of miRNA clusters in teleost.
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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 | 0.001 | 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".