Total Coliforms and Escherichia coli in Surface and Subsurface Water from a Sugarcane Agroecosystem in Veracruz, Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it