A high-quality genome assembly and annotation of Quercus acutissima Carruth
Bibliographic record
Abstract
Introduction Quercus acutissima is an economic and ecological tree species often used for afforestation of arid and semi-arid lands and is considered as an excellent tree for soil and water conservation. Methods Here, we combined PacBio long reads, Hi-C, and Illumina short reads to assemble Q. acutissima genome. Results We generated a 957.1 Mb genome with a contig N50 of 1.2 Mb and scaffold N50 of 77.0 Mb. The repetitive sequences constituted 55.63% of the genome, among which long terminal repeats were the majority and accounted for 23.07% of the genome. Ab initio, homology-based and RNA sequence-based gene prediction identified 29,889 protein-coding genes, of which 82.6% could be functionally annotated. Phylogenetic analysis showed that Q. acutissima and Q. variabilis were differentiated around 3.6 million years ago, and showed no evidence of species-specific whole genome duplication. Conclusion The assembled and annotated high-quality Q. acutissima genome not only promises to accelerate the species molecular biology studies and breeding, but also promotes genome level evolutionary studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.003 | 0.001 |
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".