Data of heavy metals in soil and groundwater at Kiwi gardens of Amlash in Guilan Province, Iran
Bibliographic record
Abstract
Data on this paper describe the concentrations of arsenic, cadmium, copper, nickel, lead and zinc in the surface soils and groundwater's of Kiwi gardens and its relation to chemical fertilizers in Amlash city, Guilan Province, in Iran. The results of this study showed that the average concentration of heavy metals in groundwater and soils of the studied areas was less than the national standards of Iran for irrigation water, Dutch MPA for soils (except Cu and Ni) and Canadian MAC for inorganic fertilizers. Considering that after fertilizing to soils used in gardening, the concentration of heavy metals in groundwater and soil can be increased significantly, so that chemical fertilizers can be considered as an effective factor in increasing the amount of heavy metals in water and soil. The results of this research can be used by who concern about water and soil quality related to fertilizing and also can be used by Rural Water and Wastewater Company and Ministry of Jahad Agriculture of Iran.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".