The Arctic charr (Salvelinus alpinus) genome and transcriptome assembly
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Arctic charr have a circumpolar distribution, persevere under extreme environmental conditions, and reach ages unknown to most other salmonids. The Salvelinus genus is primarily composed of species with genomes that are structured more like the ancestral salmonid genome than most Oncorhynchus and Salmo species of sister genera. It is thought that this aspect of the genome may be important for local adaptation (due to increased recombination) and anadromy (the migration of fish from saltwater to freshwater). In this study, we describe the generation of a new genetic map, the sequencing and assembly of the Arctic charr genome (GenBank accession: GCF_002910315.2) using the newly created genetic map and a previous genetic map, and present several analyses of the Arctic charr genes and genome assembly. The newly generated genetic map consists of 8,574 unique genetic markers and is similar to previous genetic maps with the exception of three major structural differences. The N50, identified BUSCOs, repetitive DNA content, and total size of the Arctic charr assembled genome are all comparable to other assembled salmonid genomes. An analysis to identify orthologous genes revealed that a large number of orthologs could be identified between salmonids and many appear to have highly conserved gene expression profiles between species. Comparing orthologous gene expression profiles may give us a better insight into which genes are more likely to influence species specific phenotypes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".