Bibliographic record
Abstract
This dataset contains historical snow water equivalent (SWE) simulations, produced from the Hydrotel snow module fed with meteorological observations. The simulations are provided on a 10km by 10km grid covering the southern portion of the province of Quebec, Canada and used as a proxy of SWE climatology in our adaptation of the Schaake shuffle.. The grid for the historical SWE simulation covers -81.5 to -57.1 in longitude and 43 to 53.4 in latitude, which is smaller than the meteorological grids, but for the the common portion, the grids overlap. The SWE grid has is 105 (lat) x 245 (Lon), for a total of 25725 pixels. A total of 44 years are used to produce the historical grids (1961-2004), and +/- 7 days around each of the date is used, for a total of 44years x 15 days = 660 values for each day of the year. Therefore, the dimensions of the historical SWE data is 660 x 25 725, which represents "nb of sample days x grid points).
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.029 |
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 source (direct Gemma or distilled Codex), 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".