RECLAMATION POTENTIAL OF GREEN SPACES IN NOVOCHERKASSK, ROSTOV REGION
Bibliographic record
Abstract
Purpose: to assess the reclamation potential of green spaces in Novocherkassk, Rostov region. Materials and methods. Heavy metals gross forms content determination: zinc (Zn), lead (Pb), cadmium (Cd), nickel (Ni), cobalt (Co), manganese (Mn), copper (Cu) – and their total value in the leaf mass of woody plants: horse chestnut (Aesculus hippocastanum), small-leaved linden (Tilia cordata), Norway maple (Acer platanoides), green ash (Fraxinus excelsior), black locust (Robinia pseudoacacia), Canadian poplar (Populus canadensis), growing on the territory of typical objects of park landscapes located in different parts of the city with increased technogenic load, was carried out using the method of plasma atomic absorption spectrometry (AA-method). Results. The obtained data allowed us to determine the total accumulation index of heavy metals by adding these elements together, expressed in milligrams per kilogram. The highest amount of Zn (69.01 mg/kg) is contained in the leaves of the Canadian poplar in the park of the Donskoy microdistrict, Pb (2.87 mg/kg) and Cd (0.128 mg/kg) are found in the horse chestnut in the park on Troitskaya Square. Based on the obtained data, diagrams for the content of each metal in the woody plant species accepted for the study and the total accumulation index at all study sites were constructed. Conclusions: the analyses performed to assess the metal-accumulating capacity allowed to identify woody plant species whose phytomass, under conditions of significant technogenic load, extracts heavy metals from the biogeochemical cycle to the maximum, and they can be recommended for cultivation in urbanized areas of the steppe zone in the North Caucasus.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".