Total Coliforms and Escherichia coli in Surface and Subsurface Water from a Sugarcane Agroecosystem in Veracruz, Mexico
Bibliographic record
Abstract
Water contamination is a phenomenon of global concern resulting from human activities. Coliform bacteria reduce water quality and negatively affect public health. The pollution of surface and groundwater by coliform bacteria, including Escherichia coli, originate, in general, from point sources of pollution derived from human settlements, such as those located in Module I-1, Irrigation District 035, La Antigua, Veracruz, Mexico. The objective of this study was to assess the level of contamination of surface and groundwater by coliform bacteria and E. coli, as well as to identify point sources of water contamination by these bacteria in the sugarcane agroecosystem of Irrigation Module I-1, La Antigua. Sampling sites included deep wells, irrigation canals and natural streams near point sources of pollution. The determination of total coliform bacteria and E. coli were made in accordance with Mexican Standard NMX-AA-042-1987. Total coliform results revealed differences between groundwater (198.6 MPN/100 mL) and surface water concentrations (52,419.2 MPN/100 mL) (p < 0.05), and between irrigation water (76,501.1 MPN/100 mL) and concentrations in natural streams (28,337.3 MPN/100 mL). The highest concentration of E. coli was found in groundwater and surface water samples from the municipality of La Antigua. The primary sources of contamination are the discharges from drains and septic tanks. Total coliform values exceeded permissible limits established by NOM-127-SSA1-1994 that regulates the permissible water quality limits for human use and consumption. The presence of E. coli represents a significant public health risk.
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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 | 0.001 | 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".