Meteorological, soil moisture, surface water, and groundwater data from the St. Denis National Wildlife Area, Saskatchewan, Canada
Bibliographic record
Abstract
Abstract. The St. Denis National Wildlife Area is located in the seasonally frozen and semi-arid Canadian Prairies, close to Saskatoon, Saskatchewan. The site has a hummocky terrain and is underlain by clay-rich glacial tills. Though the site is only 4 km2 it contains hundreds of wetlands containing ponds which range in size, in permanence (from ephemeral to permanent), and in their interactions with groundwater (recharge and discharge ponds are present). The site was established as a research area in 1968 and has long-term records of hydrological observations, including meteorological, snow, soil moisture, surface water (ponds) and groundwater data. Some records, notably the pond level and chemistry data, span the period 1968 to present. Other datasets, notably water level observations from networks of piezometers, have been collected sporadically at different locations and times. Some datasets are collected manually on an annual basis, including pond surveys and snow surveys. Meteorological data have been collected by automatic weather stations since 1989 and have been maintained and upgraded over time, with a flux tower added to the site in 2011. Automatically logged soil moisture profiles and collocated piezometers have been running since 2013. A lidar survey from 2005 provides a 1 m resolution digital elevation map (DEM) of the site and surrounding landscape. The compiled data are available at https://doi.org/10.20383/101.0115 (Bam et al., 2018).
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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".