Evaluation of water genotoxicity using comet assay in two freshwater fish species, Wallago attu and Ompok bimaculatus in Kabul River, Pakistan
Bibliographic record
Abstract
The investigation determines the pollution status of river Kabul and its effects on the DNA of Wallago attu and Ompok bimaculatus. River Kabul gets pollutants from Amanghar industries and sewages from Mardan, Nowshera and Peshawar. Water and fish samples are taken to study heavy metals and physical parameters. The overall sequence of physical parameters in water samples was TDS>TSS>EC>TA>Cl>Na>pH>K, and that of heavy metals was Zn>Cr>Mn> Fe>Cu>Pb>Ni>Cd. The studied parameters in all the water samples except TSS are within the proposed limits of national environmental quality standards. The overall trend of analysed water samples was C>B>A. The study determines the effects of water pollution on the DNA of Ompok bimaculatus and Wallago attu tissues. Therefore, degrees of DNA damage such as TCS and comet class are studied in gills, liver, muscles, and intestines of Wallago attu and Ompok bimaculatus. The trend of DNA damage in examined tissues was intestine>skin>liver>gills>muscle, and in studied fish species, it was Ompok bimaculatus>Wallago attu. More significant DNA damage was observed in the intestine and smaller in the muscle. More DNA damage was found in Ompok bimaculatus and less in Wallago attu. The investigation recommended detoxifying the effluents and sewages before discharging them in River Kabul.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".