Freeze–Thaw Changes of Seasonally Frozen Ground on the Tibetan Plateau from 1960 to 2014
Bibliographic record
Abstract
Abstract The freeze–thaw changes of seasonally frozen ground (SFG) are an important indicator of climate change. Based on observed daily freeze depth of SFG from meteorological stations on the Tibetan Plateau (TP) from 1960 to 2014, the spatial–temporal characteristics and trends in SFG were analyzed, and the relationships between them and climatic and geographical factors were explored. Freeze–thaw changes of SFG on a regional scale were assessed by multiple regression functions. Results showed multiyear mean maximum freeze depth, freeze–thaw duration, freeze start date, and thaw end date that demonstrate obvious distribution characteristics of climatic zones. A decreasing trend in maximum freeze depth and freeze–thaw duration occurred on the TP from 1960 to 2014. The freeze start date has been later, and the thaw end date has been significantly earlier. The freeze–thaw changes of SFG significantly affected by soil hydrothermal conditions on the TP could be assessed by elevation and latitude or by air temperature and precipitation, due to their high correlations. The regional average of maximum freeze depth and freeze–thaw duration caused by climatic and geographical factors were larger than those averaged using meteorological station data because most stations are located at lower altitudes. Maximum freeze depth and freeze–thaw duration have decreased sharply since 2000 on the entire TP. Warming and wetting conditions of the soil resulted in a significant decrease in maximum freeze depth and freeze–thaw duration in the most area of the TP, while drying soil results in a slight increase of them in the southeast of the TP.
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".