Physical-Chemical Properties and Spatial Distribution of Heavy Metals in Agriculture Soil in Al-Qadisiyah City by using ArcGIS and Multivariate Analysis
Bibliographic record
Abstract
Al-Qadisiyah governorate is one of the most important agricultural areas in Iraq, and the study was conducted in different areas of the governorate, including seven areas for sampling. The physical-chemical properties and heavy metals of agricultural soils were examined. The results showed that highest value was Ni (189.9 mg/kg) followed by Cr (124.5 mg/kg), Zn (50.8 mg/kg), Cu (36.9 mg/kg), Pb (35.2 mg/kg) and Cd (1.17 mg/kg). Moreover, Ni and Cr concentration levels were higher than Canadian soil guidelines. Geostatistical analysis was applied to know the sources of heavy metals in agricultural soil and results were revealed that Zn, Cu, Ni, and Cr were the same pollution sources and Cd and Pb also were the same pollution sources indicating these elements impacted by anthropogenic activities. The Pearson correlation coefficients found some physical-chemical properties role in increasing heavy metals in the soil such as EC and Cu, and also TOC, OM and Cr. Therefore, these results are considered useful for the competent authorities in order to reduce and control these pollutants in agricultural soils.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".