Virtual Watershed Model Simulations for Typified Prairie Watersheds in Pothole Till
Bibliographic record
Abstract
The dataset is comprised of inputs to and outputs from the Cold Regions Hydrological Model (CRHM) when it was run as a virtual model of the Pothole Till class, as defined by Wolfe et al. (2019). These watersheds represented typified prairie watersheds based on physiogeography and coherent response to environmental change. Model parameters were informed by the results of Wolfe et al. (2019). The .prj files necessary to run the virtual models are included in the dataset. Climate forcing data are from the Adjusted and Homogenized Canadian Climate Dataset from a cohort of stations contained within each watershed class and cover a period from 1960-2006. There are a series of wetland drainage scenarios that progressively reduced the wetland depression area and storage capacity by increments of 10%. Model output includes hourly catchment outflow, and depression water storage in the HRUs for the baseline and each scenario.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.005 |
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; both teacher heads agree on what is shown here.
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".