Water Quality and Trophic State of the Tourism and Agricultural Zone in Lake Yojoa
Bibliographic record
Abstract
Eutrophication, caused by excess nutrients such as phosphorus and nitrogen, alters the physical, chemical, and biological characteristics of water, negatively affecting biodiversity.This phenomenon, exacerbated by human activities such as agriculture and tourism, poses a growing threat to Lake Yojoa, the only significant freshwater body in Honduras.Population growth and human practices have raised nutrient levels, deteriorating water quality.This study evaluated the state of the lake using the Water Quality Index of the Canadian Council of Ministers of the Environment (WQI-CCME) and other trophic indices.Two analysis zones were established: Zone A, related to tourism, and Zone B, linked to agriculture.During 2023, quarterly sampling was carried out and eight physicochemical parameters were analyzed, such as pH, dissolved oxygen (DO), and total nitrogen (TN).The results showed "poor" quality in Zone A (WQI of 44) and "marginal" quality in Zone B (WQI of 45).According to the Carlson index, both zones were classified as eutrophic, indicating a high presence of nutrients and algae proliferation, confirmed by the attenuation coefficient (K).The T-test revealed significant differences in TN, with higher concentrations in Zone A, suggesting that tourism has a more negative influence than agriculture on the eutrophication of the lake.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".