Land Use and Water Quality Relationships in the Lower Little Bow River Watershed, Alberta, Canada
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
Abstract Water quality in the Lower Little Bow River was monitored to determine if irrigation return flow streams had a significant impact on river water quality and to examine relationships between land use and water quality in this diverse agricultural watershed. Water samples were collected weekly or biweekly during the irrigation season and monthly in winter for three years. A comprehensive land use assessment was also completed. Significant differences in flows, and in nutrient and bacteria loads, were found along the mainstem of the river following the inflows of irrigation return water; however, differences in concentrations were only significant in a drought year when mainstem flows were reduced. Pearson correlations among land use, soil types, and water quality variables identified significant positive relationships between the proportion of cereals, irrigated land, and confined feeding operation (CFO) density and maximum concentrations of total nitrogen (TN), nitrate-nitrogen, and total phosphorus (TP) that were observed during runoff events. Most nutrient variables were inversely related to the proportion of native prairie. The variation in maximum TP and median dissolved P concentrations was largely explained by the proportion of cereals in the sub-basin, while the variation in maximum and median TN concentrations was explained by the proportions of irrigated land and native prairie, respectively. Microbiological variables were not related to any of the measured variables, suggesting that factors influencing bacteria populations operate at different scales.
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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 | 0.012 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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