Analysis of genetic diversity of <i>Lactarius hatsudake</i> in South China
Bibliographic record
Abstract
Lactarius hatsudake is a type of ectomycorrhizal fungus that significantly influences the growth of pine trees. It is widely prevalent in Asian countries and has a high economic value. Artificial cultivation of this fungus has not been achieved as yet; therefore, excessive manual harvesting may cause serious damages to the site of its production. In this study, we analyzed 41 samples of L. hatsudake from south China using internal transcribed spacer (ITS) sequences. By comparing the differences among ITS sequences to identify the haplotype diversity within each population, the relationships among local populations, the relationship between the level of genetic differentiation and geographical separation, and the contributions of local and regional geographical separations to the overall ITS haplotype variation were analyzed. Genetic analysis indicates that ITS sequences obtained from these 41 L. hatsudake samples could be identified as 18 haplotypes, of which 13 haplotypes were contained in only a single sample, whereas the remaining sequence types all were contained in two or more samples. The most common sequence type, haplotype 6, was found in 16 samples and was distributed across nearly every region. The Mantel test demonstrated that there is no significant linear relationship between geographical distance and the F(ST) value of genetic difference. Results of this research illustrates that there exists a certain degree of genetic intermixing among natural populations of L. hatsudake. From the group genetic analysis, it appears that there exists genetic differentiation of lower frequencies in natural populations of L. hatsudake; however, the linear relationship between the degree of genetic differentiation and geographical distance is not distinctly apparent.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".