The Identification of Araliaceae Species by ITS2 Genetic Barcoding and Pollen Morphology
Bibliographic record
Abstract
Abstract The genetic barcode ITS2 (ITS: internal transcribed spacer) and pollen morphology were used for the identification of the pharmacologically valuable wild Araliaceae species Panax ginseng, Oplopanax elatus, Aralia elata, Aralia continentalis, Eleutherococcus senticosus, and Eleutherococcus sessiliflorus inhabiting the natural forests of Primorye, Russia. The ITS2 locus successfully identified all six species, which supports the use of ITS2 as a standard barcode for medicinal plants. However, the ITS2 locus was insufficient for intra-specific discrimination in these species, neither within Primorye nor from other world representatives within GenBank. Araliaceae pollen was confirmed to undergo size-reducing metamorphosis. The final morphotypes were species-specific for each of the six species but could not discriminate intra-species geographic localities within Primorye. The morphologies of the final pollen morphotypes from homologous species inhabiting other parts of the world are not yet known. Therefore, whether pollen is applicable for Araliaceae intra-species discrimination between Primorye and other world localities could not be established. Based on these findings, we propose that the ITS2 genetic barcode and the final pollen morphotypes are suitable for the identification of Araliaceae species. However, further studies will be needed to determine the suitability of genetic and pollen traits for Araliaceae geographic authentication.
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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 | 0.001 |
| 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 | 0.001 |
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".