Dataset of high-frequency water quality and meteorological variables in Buffalo Pound Lake, Saskatchewan, Canada, 2014 – 2021
Bibliographic record
Abstract
Lakes can undergo rapid changes that are not captured during traditional, discrete sampling campaigns. Sensor-based data provide opportunities to understand these rapid changes in lakes. Here, we present eight years of sensor-based monitoring data from the open water season in a shallow, polymictic reservoir in southern Saskatchewan, which serves as an important drinking water supply. A monitoring buoy was moored annually at the same site providing sensor data including photosynthetically active radiation (PAR; 0.62 and 0.78 m below surface), pH, dissolved oxygen, turbidity, specific conductivity, phycocyanin and chlorophyll (0.8, or 0.8 and 2.8 m below surface), and temperature (multiple locations in the water column) at high frequency. The buoy was also equipped with a weather station to record air temperature, barometric pressure, PAR, rain, relative humidity, wind direction and wind speed. Data were reviewed for data quality. This long-term dataset can be used to understand thermal variation, chemical and ecological change, and to characterize the often rapid changes that polymictic lakes undergo, particularly those resulting from seasonal changes and development of cyanobacterial blooms.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".