Analysis of genetic population structure and diversity in<i>Mallotus oblongifolius</i>using ISSR and SRAP markers
Bibliographic record
Abstract
Background Mallotus oblongifolius, an evergreen shrub endemic to Hainan Island, China, is important both medicinally and economically. Due to its special medicinal significance and the continuing rise of market demand, its populations in the wild have been subject to long-term illegal and unrestrained collection. Hence, an evaluation of genetic variability is essential for the conservation and genetic reserve development of this species. Methods Sequence-related amplified polymorphism (SRAP) and inter-simple sequence repeat (ISSR) markers were employed to assess the genetic diversity and genetic structure of 20 natural populations ofM. oblongifoliusgrowing in different eco-geographical regions of Hainan Island, China. Results We revealed a considerable genetic diversity (h= 0.336,I= 0.5057, SRAP markers;h= 0.3068,I= 0.4657, ISSR markers) and weak genetic differentiation (Gst = 0.2764 for SRAP, Gst = 0.2709 for ISSR) with the same gene flow (Nm = 1.3092 for SRAP, Nm = 1.346 for ISSR) among theM. oblongifoliuspopulations. The Mantel Test showed that the distribution of genetic variation among populations could not be explained by the pronounced geographical distances (r= 0.01255,p= 0.5538). All results of the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), Neighbor-joining (NJ), Principal Coordinate Analysis (PCoA) and Bayesian analyses supported a habitat-specific genetic clustering model forM. oblongifolius, indicating a local adaptive divergence for the studied populations. Discussion We suggested that the habitat fragmentation and specificity forM. oblongifoliuspopulations weakened the natural gene flow and promoted an adaptation to special habitats, which was the main reason for local adaptive divergence amongM. oblongifolius.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.002 | 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".