DEVELOPMENT OF METHODOLOGY FOR THE ANALYSIS OF WATER QUALITY IN RIVERS
Bibliographic record
Abstract
The Bermejo River, located in the San Pedro Sula region of Honduras, is a vital resource for the city and its economy, playing a crucial role in commercial activities and meeting basic needs, particularly in communities lacking proper access to water infrastructure.Despite its significance, there is a notable lack of information regarding the water quality in this river.This research aims to develop a detailed method that serves as a guide for future water quality analyses in rivers including Bermejo.The necessary procedures for sample collection are outlined, along with strategically selected sampling points.Parameters to be assessed include the presence of detergents and chlorine, indicators of fecal contamination, chemical oxygen demand, dissolved oxygen concentration, presence of fats and oils, pH levels, and fecal coliforms.The designated sampling points for this study are point a, located at coordinates 15°31'56.6"N88°00'51.8"W,and point b, at 15°30'46.2"N87°59'33.5"W.Once data is collected and results of tests for each parameter are analyzed, the Canadian council of ministers of the environment water quality index (CCME WQI) is applied.The results yielded a score of 29.51, indicating that the water quality falls into the lowest category, considered poor.This study provides a systematic initial insight into the water quality of the Bermejo River and establishes the groundwork for future research and monitoring.The findings underscore the need for interventions and policies addressing pollution sources and promoting improvements in the water quality of this crucial resource for the community.
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.
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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".