Lead Pollution Measurement Along National Highway and Motorway in Punjab, Pakistan
Bibliographic record
Abstract
A study was conducted to determine qualitative and quantitative lead contamination in soil and vegetation along two major roadsides of Pakistan using Atomic Absorption Spectroscopy. There has been a rapid increase in vehicles on the highways using petroleum products, which has caused considerable raised the quantity of lead in the atmosphere increasing the risk to health. Laser Induced Breakdown Spectroscopy (LIBS) was used as multi elemental analysis technique to cross confirm the lead contamination in the samples. The samples of soil and grass were collected from each location 100m away from the edge of roads at every 25m. The levels of lead were found to be 125mg/kg to 87mg/kg respectively in soil and grass. Hence there is high accumulation of lead in roadside soil and vegetation of linking roads of highly populated cities of Pakistan, Faisalabad and Lahore.
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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 | 0.007 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".