Molecular identification of endangered Korean lady’s slipper orchids (<i>Cypripedium</i>, Orchidaceae) and related taxa
Bibliographic record
Abstract
Reliable and accurate species identification is essential to establish a strategy for monitoring and manipulation of plant populations for conservation biology. However, identification of nonflowering plants is difficult. Based on recent advances in molecular biological techniques, various molecular identification methodologies have been proposed and applied in plant science, with a focus on medicinally valuable species. Lady’s slipper orchids (Cypripedium) are a representative terrestrial orchid group that includes many endangered species. Of 46 species, 3 (Cypripedium japonicum Thunb., Cypripedium macranthos Sw., and Cypripedium guttatum var. koreanum Nakai) were reported from Korea and categorised as endangered species or at risk of becoming endangered because of the rapidly decreasing population. We generated an accurate molecular identification system for these species using the sequence variation and species-specific SNPs of two plastid loci, rpoC2 and the IGS region between atpF and atpH. We selected the atpF-H region for molecular identification of the Korean Cypripedium and related Taiwan-endemic taxon Cypripedium formosanum Hayata. Cypripedium guttatum var. koreanum contained large deletions of over 300 bp, and could be distinguished by electrophoresis. For the other three species, we designed new primers based on a specific insertion (C. macranthos) and SNPs (C. japonicum and C. formosanum). We confirmed that molecular identification enables detection of each species using species-specific primers.
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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 | 0.000 |
| 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".