Occurrence and Risk Assessment of Organochlorine Pesticides (OCPs) in Surface Water of Veeranam Lake, Tamil Nadu
Bibliographic record
Abstract
The study aimed at assessing the levels of organochlorine pesticide (OCPs) residues in the surface water of Veeranam Lake, Tamil Nadu, South India and its effects on human beings and aquatic organisms. Pesticide residues were quantified using Gas Chromatograph Mass Spectrometer (GCMS) in Quadrupole analyzer on Electron Ionization (EI) mode. The measured environmental concentration (MEC) of OCPs in the water samples was taken for calculating the carcinogenic risk and ecological risk quotient (ErQ). The most commonly encountered organochlorine pesticides (OCPs) in surface water of Veeranam Lake were isomers of DDT (p, p?-DDD & o, p?-DDT) and HCH (? & ?) compounds, aldrin, dieldrin and mirex. The mean concentrations of endrin exceed the permissible limit of Canadian guidelines for fresh water (CGFW). The results of the present investigation showed that the carcinogenic risk among local population through intake of water from Veeranam Lake is more likely due to presence of significant levels of aldrin and mirex. The result also demonstrated acute risk to aquatic animals as a result of high concentrations of aldrin and endrin. Even though the incidence percentage of DDT (p, p?-DDD & o, p?-DDT), HCH (? & ?), aldrin, dieldrin and mirex were high, their mean concentrations are well below the international permissible limit (CGFW) except endrin. However, these minimal levels of aldrin and mirex were supposed to cause carcinogenic risk and ecological risk to humans and aquatic organisms respectively.
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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 | 0.008 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".