ASSESSMENT AND SPATIAL DISTRIBUTION OF NIKLE WITHIN SOILS OF IBSHWAY DISTRICT AREA, FAYOUM GOVERNORATE, EGYPT
Bibliographic record
Abstract
Spatial distribution of Ni has been studied in soils of Ibshway district area, Fayoum governorate, Egypt using grid system- log distance of 2 km. Levels and Spatial distribution of Ni( total and extractable) contents were identified and mapped using "ILWIS application" Geographic Information System (on basis of their Ni contents) throughout the studied area. It was found that the mean concentrations of total Ni within the top 60 cm of soils were 40.02 mg kg-1 , i.e higher than the general means in some soils of the world. The general mean concentrations of total Ni within the top 60 cm in Ibshway District soils mostly higher than the maximum allowable limits applied in some countries such as Denmark , Netherlands , Germany , Ireland and Canada the total Ni values are similar to the permissible limits applied in some developed countries such as Finland and below the allowed maximum limits applied in some developed countries such as Switzerland, Czech Republic and Eastern Europe (Russia, Ukraine, Moldavia and Belarus) The maps generated through GIS are useful for decision makers for land use planning, conservation and evaluating the degree of environmental contamination with hazardous heavy metals.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".