The Impacts of Land Use and Groundwater Inputs on Stream Health and Habitat of Jennings Creek, Bowling Green, Kentucky
Bibliographic record
Abstract
In Bowling Green, Kentucky, the Jennings Creek watershed encompasses the entire city and surrounding area; however, little work has been completed focused on assessing the Creek’s water quality, habitat, and biological indicators. Jennings Creek is fed by several karst groundwater springs, making it highly vulnerable to contamination due to the rapid connection between the surface and subsurface via sinkholes and underground rivers. An examination of Jennings Creek’s water quality, habitat, and biological indicators provides an assessment of the watershed’s health. The methodology closely followed the methods for assessing habitat by Kentucky’s Energy and Environment Cabinet and was approved for the EPA 319(h) Watershed Plan project underway for Jennings Creek. Three study sites were identified along Jennings Creek for assessment with concurrent water quality sampling. Following sampling, each site received overall scores for habitat health, biological health, and water quality. An overall water quality score for each of the three stream sites was calculated using the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). A comparative analysis of all sites was then completed by comparing the scores and corresponding ratings. Overall, all sites received poor habitat assessment ratings and marginal Water Quality Index ratings. This is likely due to the high degree of urbanization in the surrounding environment, which increases the risk of pollutants entering the watershed. Both the New Spring and Creekwood sites received poor biological assessment ratings, while Russell Sims received a marginal rating. Through comparative analysis, Russell Sims scored the highest. This is potentially explained by the urbanization and water quality issues faced by New Spring and Creekwood. All sites scored relatively low, highlighting the need for a comprehensive watershed plan.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".