Correlation of soil magnetic susceptibility with heavy metals and physico-chemical profile
Bibliographic record
Abstract
The present study was conducted to determine magnetic susceptibility and its correlation with the concentration of selected heavy metals, including arsenic, chromium, cadmium and lead, as well as the physico-chemical properties of topsoil samples collected from District 5 of Tehran Municipality, Iran. The specimens were collected from 13 stations (0–10 cm depth), and the location of the sampling points was recorded as well using the Global Positioning System. The specimens were then analysed for physico-chemical properties, heavy metal concentration (by atomic absorption spectrometry) and in situ magnetic susceptibility at low frequency (χ lf , using a Bartington MS2 dual-frequency sensor). According to the results, the highest and lowest χ lf values were 34.1 × 10 −8 and 16.3 × 10 −8 m 3 /kg at stations 3 (Azadi bus station) and 11 (Jannatabad neighbourhood), respectively. A significant correlation was found between χ lf and the concentration of lead and chromium (P < 0.05). Moreover, there was a positive and significant correlation between χ lf and the soil organic matter in the study area (P < 0.01). Based on the research findings, the magnetic susceptibility measure can be used to evaluate quickly the level of soil contamination with heavy metals and also to monitor the changes in soil organic matter.
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".