Accumulation of chemical elements in the roots of <I>Euphorbia fischeriana</I> Steudel in the Shilka river basin (Transbaikal region)
Bibliographic record
Abstract
Background. Euphorbia fischeriana Steudel is used in traditional and herbal medicine in Russia and China. Its roots contain 241 chemical components, but there is not enough knowledge about the plant’s elemental composition. Concentrations of chemical elements in plants have an impact the effectiveness of medical products. Materials and methods. The research was conducted in the Transbaikal region. Plants were analyzed using an ICP-MS Elan 9000 mass spectrometer (Canada). The ICP-MS method of measuring metal content in solid objects, PND F 16.1:2.3:3.11-98 was used. Chemical analysis of the soil was performed at Kostromskaya State Station of Agrochemical Service. The obtained data were statistically processed using the Microsoft Excel software. Results. The accumulation of macro- and microelements in plant roots was studied (Ca, P, Mg, Na, Fe, Mn, Zn, Mo, Cr, Co, Se, Cu, B, Ni, V, As, Li, Pb, Ba, Bi, Cd, Hg, Be, Sb, Rb, Zr, Sn, Ag, W, Sr, and Ti). The chemical elements whose concentrations were significantly higher or, contrariwise, lower than the clarke of terrestrial plants were identified. Accumulations of Ti, Ag, As, Cr, Sr, Li, Ba, Mo, Fe, Bi, and Sb in descending order were 2–14 times higher than the clarke of terrestrial plants. Concentrations of Mn, Cd, Se, and especially V and Cu in E. fischeriana roots were low (0.01–5% of the clarke). The concentration of As in the test areas exceeded the threshold limit value for medicinal herbage and medicinal plant products (OFS.1.5.3.0009.15). Conclusion. The study made it possible to find deficiencies of a number of vital elements in E. fischeriana roots, discrepancy between the tested herbage and the threshold limit value for As, and increased accumulation of a number of toxic and potentially toxic elements compared with the clarke.
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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) | 0.000 | 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".