BTEX contamination of Bengaluru aquifers, Karnataka, India
Bibliographic record
Abstract
Leakage from underground storage tanks (USTs) in petrol filling stations is a recognised pathway for contamination of aquifers by benzene, toluene, ethylbenzene and xylene (BTEX) compounds. Bengaluru City, India, partially depends on groundwater for potable water and has a specific climatic condition of wet and dry seasons. Hence, the influence of temporal rainfall variations on possible BTEX contamination of groundwater from leaky USTs was examined by testing tube-well samples located at petrol filling stations and their vicinities in Bengaluru City during pre- and post-monsoon periods. Groundwater samples were collected from tube wells located at petrol filling stations or their vicinities during post-monsoon (September 2015–January 2016) and subsequent pre-monsoon (March–April 2016) periods. Variations in BTEX concentrations during post- and pre-monsoon periods highlighted the influence of season on BTEX concentrations in the aquifer, as higher BTEX concentrations were generally observed in groundwater samples during post-monsoon than pre-monsoon. The results of the study show that BTEX contamination of Bengaluru aquifers from leaky USTs in petrol filling stations is not extensive as only 5% of groundwater samples showed benzene presence in excess of the permissible limit, while toluene, ethylbenzene and xylene compounds were below permissible limit in all the 124 groundwater samples.
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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 | 0.001 | 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".