A reference genome for Bluegill Sunfish (Centrarchidae: Lepomis macrochirus)
Bibliographic record
Abstract
North American sunfishes (Family Centrarchidae) are among the most popular sportfish throughout the United States and Canada. Despite the popularity of sunfishes, their ecological importance, and their extensive stocking and aquacultural history, few molecular studies have examined the evolutionary relationships and species limits among members of this group, many of which are known to hybridize. Here, we describe a chromosome-scale, genome assembly representing Bluegill Sunfish (Lepomis macrochirus), one of the most widespread centrarchid species. By combining long-read, Oxford Nanopore sequencing data with short-insert, whole genome and HiC sequence reads, we produced an assembly (Lm_LA_1.0) having a total length of 889 MBP including 1,841 scaffolds and having a scaffold N50 of 36 MBP, L50 of 12, N90 of 29 MBP, and L90 of 22. BUSCO analyses indicated that Lm_LA_1.0 was relatively complete with 99% (eukaryota_odb10) and 98% (actinopterygii_odb10) BUSCOs detected, and ab initiogene prediction performed using this new assembly identified a set of 15,873 genes that were supported by external data. This new assembly provides an important addition to the growing set of assemblies already available for spiny-rayed fishes (Acanthomorpha), and it will serve as a resource for future studies that focus on the complex evolutionary history of centrarchids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".