Assessment of the genetic diversity and population structure of Maire yew (<i>Taxus chinensis</i> var. <i>mairei</i>) for conservation purposes
Bibliographic record
Abstract
Maire yew (Taxus chinensis var. mairei (Lemée et Lévl) Cheng et L.K. Fu) is an endangered coniferous species in China. We examined the genetic pattern of Maire yew populations and explored any genetic variation among three groups (Core, Edge, and Disturb) based on hemeroby. Twenty-five populations (533 individuals) were analyzed using nuclear and mitochondrial simple sequence repeat (nSSR and mtSSR, respectively) markers and chloroplast DNA (cpDNA) sequences. nSSR marker analysis indicated a moderate level of genetic diversity (He = 0.467), a high level of biparental inbreeding within populations (FIS = 0.314; P < 0.01), and a strong genetic differentiation among populations (FST = 0.161). Restricted gene flow due to mating characteristics and long-term isolation is the main factor affecting the natural genetic pattern. Our study suggested that human influence had a strong effect on the genetic diversity and differentiation. The results based on nSSR analysis showed that the human-influenced populations (Distub group) had the highest genetic diversity (He = 0.500, Ar = 3.790) and the lowest genetic differentiation (FST = 0.062) among populations compared with that of the natural populations (Core group, He = 0.463, Ar = 3.148, FST = 0.221). However, the analysis of cpDNA sequences showed an opposite trend on genetic diversity. The information presented here can supply the basis for genetic guidelines for appropriate conservation programs.
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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 | 0.000 | 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".