South Saskatchewan River Basin nitrate source isotope tracing
Bibliographic record
Abstract
This research project sampled 17 mainstem sites of the Bow River and Oldman River, part of the South Saskatchewan River basin in Alberta, during high and low discharge periods in 2014 and 2015. Riverine nitrate and boron concentrations, mean daily flux, major ion chemistry, and stable isotope measurements of nitrogen-15 of nitrate, oxygen-18 of nitrate, and boron-11 of dissolved boron were determined and compared against results for effluent from seven local wastewater treatment plants (WWTPs), eight synthetic fertilizers, cow manure, and three predominantly agricultural tributary sites to estimate point and non-point nitrate sources using a combined isotope tracing approach. Only river mainstem and tributary chemistry is included in this dataset, please contact the data steward for more data including point and non-point sources. The results of the study indicated WWTP effluent was the key nutrient source in the Bow River downstream of Calgary and manure-derived nutrients affect the Bow and Oldman Rivers in agricultural regions. Overall, boron was proven to be an effective co-tracer for discriminating between urban and agricultural sources of nitrate in a large, mixed-use watershed. We would like to acknowledge co-authors Dr. Bernhard Mayer and Michael Nightingale of the University of Calgary Applied Geochemistry Group and Dr. Patrick Laceby of Alberta Environment and Protected Areas for their significant contributions to this research. We are grateful to Steve Taylor, Jesusa Pontoy, Andrew Kingston, Kerri Miller, and Michael Wieser who provided laboratory analysis expertise and assistance. We would also like to thank Veronique Lajciak (Fau) and Nadine Taube who assisted with field logistics and collection of water samples. This study was supported by a NSERC Discovery Grant awarded to Bernhard Mayer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".