Ensemble Mean Reanalysis Soil Temperature Dataset at 1 degree latitude/longitude resolution (60 South to 90 North), 1981 - 2018.
Bibliographic record
Abstract
This dataset accompanies Herrington, T., Fletcher, C. and Kropp, H. (in Review). The Cryosphere. It is a 1 degree ensemble mean soil temperature of the 8 reanalysis and LDAS products (based on CFSR, ERA5, ERA5-Land, ERA-Interim, GLDAS-CLSM, GLDAS-Noah, JRA-55 and MERRA2), averaged over the near surface (0 - 30 centimeter, cm) and at depth (30 cm - 300 cm), between 1981-2018. All reanalysis products were remapped using a conservative remapping technique to a resolution of 1 degree latitude and longitude, based on the GLDAS-CLSM land-mask. The ensemble mean is calculated as a simple arithmetic mean of all eight products at each timestep for all grid cells that include valid soil temperature measurements for all 8 products.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.037 | 0.031 |
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".