Distribution and ecotoxicological concerns of persistent organic pollutants in sediment from creek ecosystem
Bibliographic record
Abstract
In order to study the distribution and ecotoxicological concerns of persistent organic pollutants, grab sediment samples were collected from different locations across Thane creek, India. Analyses of samples were carried out using gas chromatography (GC)-electron capture detector and GC-mass spectrometry techniques. In organochlorine pesticides (OCPs), DDT (1,1,1,-trichloro-2,2-bis(p-chlorophenyl) ethane), DDE (1,1-dichloro-2,2-bis(p-chlorophenyl) ethylene), DDD (1-chloro-4-(2,2-dichloro-1-(4-chlorophenyl)ethyl) benzene) and α, β, and γ conformer of hexachlorocyclohexane (HCH), and 9 polychlorinated biphenyls (PCBs) congeners were analyzed in surface sediment samples. Concentrations of these pollutants in grab sediment samples may indicate their current use and impact on marine ecosystem. Average concentrations of total DDT (including DDD and DDE), HCH, and Σ9PCBs were found to be 4.9, 12.5, and 2.9 µg kg(-1)(dry weight) respectively. High concentrations of OCPs and PCBs were found at discharge locations in creek compared to other locations. Location-wise distribution of OCPs and PCBs indicates their high concentrations at the waste water receiving point. Data were compared for ecotoxicological impacts based on the levels specified in the sediment quality standards of the US Environmental Protection Agency and the Canadian Council of Ministers of the Environment. γ-HCH was found to have maximum potential to induce ecotoxicological impacts.
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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 | 0.002 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".