Water quality parameters and constituent concentrations measured in the Peel and Arctic Red Rivers, 2007–2010
Bibliographic record
Abstract
Outflow from north-flowing circumpolar rivers has a strong influence on the Arctic Ocean. The Peel and Arctic Red Rivers are tributaries of the Mackenzie Delta, a large, lake-rich floodplain that forms the interface between the Mackenzie River and the Beaufort Sea basin of the Arctic Ocean. Here, we present water quality data that were collected from the Peel and Arctic Red Rivers between 2007 and 2010 as part of an International Polar Year project that investigated the seasonal hydrology and biogeochemistry of the Mackenzie River and its delta. The Peel River was sampled 57 times between May 2007 and September 2010 upstream of the community of Fort McPherson, Northwest Territories (NT), while the Arctic Red River was sampled 32 times between May 2007 and August 2008 (with one additional sample in June 2010) approximately 0.5 km upstream of its confluence with the Mackenzie River near the community of Tsiigehtchic, NT. Each water sample was analyzed for up to 22 water quality parameters, including water temperature, specific conductivity, pH, chlorophyll a, total suspended sediments, particulate nutrients (carbon, nitrogen, and phosphorus), soluble reactive silica, major ions (calcium, magnesium, potassium, sodium, chloride, and sulfate), dissolved carbon (inorganic and organic fractions), and dissolved nutrients (three nitrogen and two phosphorus fractions). This data set, which is available for download and reuse, provides important baseline information about water quality in the Peel and Arctic Red Rivers, complements other data that have been collected in these watersheds, and will be of interest to researchers, resource managers, Indigenous organizations, and governments that are active in the region.
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 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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".