Characteristics of maximum and minimum temperature change in Dunhuang oasis in recent 55 years
Bibliographic record
Abstract
Based on the monthly mean maximum and minimum temperatures data in Dunhuang oasis during 1951 ～2005,the change trend and characteristics of annual,seasonal mean maximum and minimum temperature in Dunhuang oasis were analyzed.The analysis result showed that both maximum and minimum temperatures were increasing for the period.The minimum temperature increased more than maximum temperature and the rate of increase of minimum temperature was 13.24 times higher than that of maximum temperature.So the minimum temperature has been greatly influencing the increasing of the whole temperatures.The mean maximum temperature was increasing in spring,autumn and winter,but it was slightly decreasing in summer in Dunhuang oasis.Anyway,the mean minimum temperature was increasing in all seasons.The increase of the mean minimum tem-peratures was a mutated phenomenon.The mean minimum temperature happened in 1994 in Dunhunag oasis.
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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) | 0.000 | 0.000 |
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".