Genome size estimation of Chinese cultured artemisia annua L.
Bibliographic record
Abstract
Almost all of antimalarial artemisinin is extracted from the traditional Chinese medicinal plant Artemisia annua L. However, under the condition of insufficient genomic information and unresolved genetic backgrounds, regulatory mechanism of artemisinin biosynthetic pathway has not yet been clear. The genome size of genuine A. annua plants is an especially important and fundamental parameter, which helpful for further insight into genomic studies of artemisinin biosynthesis and improvement. In current study, all those genome sizes of A. annua samples collected with Barcoding identification were evaluated to be 1.38-1.49 Gb by Flow Cytometry (FCM) with Nipponbare as the benchmark calibration standard and soybean and maize as two internal standards individually and simultaneously. The genome estimation of seven A. annua strains came from five China provinces (Shandong, Hunan, Chongqing, Sichuan, and Hainan) with a low coefficient of variation (CV, ≤ 2.96%) wasrelative accurate, 12.87% (220 Mb) less than previous reports about a foreign A. annua species with a single control. It facilitated the schedule of A. annua whole genome sequencing project, optimization of assembly methods and insight into its subsequent genetics and evolution.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".