DNA damage in earthworms (<i>Eisenia</i>spp.) as an indicator of environmental stress in the industrial zone of Coatzacoalcos, Veracruz, Mexico
Bibliographic record
Abstract
Coatzacoalcos, Veracruz is one of the major industrial areas of Mexico. Presently, the Coatzacoalcos River and the areas surrounding the industrial complex are considered by various authors to be some of most polluted sites in Mexico. The objective of this study was to determine if earthworms could be used as indicators of environmental stress in the Coatzacoalcos industrial zone. Often, detritivores and decomposers such as earthworms are the first to be affected when the soil is contaminated. We collected soil samples to be used for persistent organic pollutants (POPs) quantification by gas chromatography. Concentrations of hexachlorobenzene, lindane and total polychlorinated biphenyls (PCBs) in the soil were above the maximum permissible limits of the Canadian Environmental Quality Guidelines (CEQG). Comet assay was conducted in coelomocytes of wild earthworms collected in Coatzacoalcos and compared with the control earthworms. We found DNA damage in earthworms from Coatzacoalcos that was significantly higher (P < 0.05) in comparison to laboratory earthworms. Earthworms are an appropriate organism to use as an indicator of environmental impact in contaminated sites. DNA damage recorded in the earthworms provides clear evidence of environmental impacts by the chemical industry on the wildlife of this region.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".