A Daily Soil Temperature Dataset and Soil Temperature Climatology of the Contiguous United States
Bibliographic record
Abstract
3Although affected by atmospheric circulation, variations in soil temperature result primarily from the radiation and sensible and latent heat exchanges at the surface and heat transfer in the soils of different thermal properties. Thus soil temperature and its variation at various depths are unique parameters useful in understanding both the surface energy processes and regional environmental and climate conditions. Yet, despite the importance, long-term quality data of soil temperatures are not available for the United States. The goal of this study is to fill this data gap and develop a soil temperature dataset from the historical data of U.S. cooperative stations. Cooperative stations ’ soil temperatures at various depths from 1967 to 2002 are collected and examined by a set of quality checks, and erroneous data of extended periods are estimated using methods constructed in this study. After the quality control, the data are used to describe the soil temperature climatology as well as soil temperature change in the continuous United States. The 35-year climatology shows that the annual soil temperature at 10cm depth, where most stations have soil temperature measurements, decreases gradually from 297
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".