Data sets for the Upper Penticton Creek watershed experiment: A paired‐catchment study to support investigations of watershed response to forest dynamics and climatic variability in an inland snow‐dominated region
Bibliographic record
Abstract
Abstract The Upper Penticton Creek watershed experiment is one of a handful of forestry‐focused paired catchment experiments in the snow‐dominated zone of western North America. The study involves an undisturbed control catchment and two treatment catchments. Streamflow has been monitored at weirs on all three streams since 1985. Following a pre‐harvest monitoring period, the treatment catchments were subject to clearcut harvesting in multiple passes that cumulatively covered ~50% of the catchments. In addition to streamflow, available hydrometeorological data sets include weather observations, snowpack water equivalent, rainfall interception, soil water content and water table levels in soil piezometers and bedrock wells. The data archive also includes digital elevation models, a Lidar‐derived image of tree heights in 2016, and vector data associated with lakes and reservoirs, the stream network, clearcut boundaries, a soil map and the logging road network. Together, these data sets provide a basis for empirical analyses of hydrological response to forest dynamics and climatic variability, and for calibration and testing hydrological models using internal variables. They should also provide useful data sets for educational purposes. Novelty Statement Upper Penticton Creek is the only long‐term, snowmelt‐dominated, experimental paired catchment study in western Canada and one of only a few in western North America. Four decades of environmental monitoring and research at this site provide an important data set to support analysis and modelling of hydrologica response to forest disturbance and climatic variability.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".