Genetic structure and barcode identification of an endangered orchid species,<i>Liparis loeselii</i>, in Poland
Bibliographic record
Abstract
The genetic diversity of five populations of Liparis loeselii from two regions of Poland, Podlachia and Silesia, was compared with respect to minisatellite markers. Moreover, the standard 2-loci barcode DNA regions, rbcL and matK genes, as well as an additional region trnL-F from chloroplast and ITS2 from nuclear genome were studied. The total genetic diversity at the species level amounted to HT = 0.356. The analysis of molecular variance revealed that 58% of genetic variation was distributed within populations, 2% among populations, and 40% between regions from NE Poland (Podlachia), and S Poland (Silesia). Nei's genetic distances indicated that specimens from the Podlachia population were genetically isolated from Silesian ones. Two genetic barriers among the studied populations were found: one barrier separated the Podlachian population from all Silesian populations and another barrier divided Kuźnica Warężyńska population from other Silesian populations. Based on barcode sequences it was found that all the examined samples were identical with respect to all the studied DNA regions. Liparis loeselii trnL-F region sequences were detected for the first time and they can be useful as complementary barcodes for this species. The analysed sequences of L. loeselii are fully consistent with sequences of specimens originating from the UK, Canada, Czech Republic, Hungary, Sweden, Italy, and Russia.
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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) | 0.000 | 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".