A long-term, temporally consistent, gridded daily meteorological dataset for northwestern North America
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
region has high topographic relief, seasonal snowpack, permafrost and glaciers, crosses multiple jurisdictional boundaries and contains the entire Yukon, Mackenzie, Saskatchewan, Fraser and Columbia drainages. We interpolate daily station data to 1/16° spatial resolution using a high-resolution monthly 1971-2000 climatology as a predictor in a thin-plate spline interpolating algorithm. Only temporally consistent climate stations with at least 40 years of record are included. Our approach is designed to produce a dataset well suited for driving hydrological models and training statistical downscaling schemes. We compare our results to two commonly used datasets and show improved performance for climate means, extremes and variability. When used to drive a hydrologic model, our dataset also outperforms these datasets for runoff ratios and streamflow trends in several, high elevation, sub-basins of the Fraser River.
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.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it