Heavy Metals Contents in Ziziphus Tree Leaves Under the Effect of Different Industrial Activities
Bibliographic record
Abstract
Effects of 3 industrial activities on the concentrations of toxic metals (Cd, Cr, Ni and Pb) and micro-nutrients elements (Fe, Cu, Zn and Mn) in the leaves of 2 and 4 years old Ziziphus trees grown closed to these industrial areas were studied during March 2013. The highest Cd, Cr, Ni and Pb concentrations in the Ziziphus leaves were found in the trees closed the paints, chemical and paper industrial sectors with values of 4.56, 8.69, 6.15 and 48.47 mg/kg, respectively, while the trees in the control area had 1.09, 1.16, 1.34 and 6.27 mg/kg, respectively. The sector of mineralization, plastic and building materials was the highest in Fe, Cu, Zn and Mn emission pollutants accumulated and absorped by the tree leaves. The 4-years old tree leaves were significantly higher than the 2-years old tree in all studied toxic and micro-nutrients elements.
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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 | 0.000 | 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".