Analysis of change characteristics of sunshine hour in Dunhuang oasis in recent 54 years
Bibliographic record
Abstract
The climate change characteristics of annual,seasonal sunshine hour in Dunhuang oasis were analyzed based on the observed data of sunshine hour in Dunhuang Oasis in recent 55 years using the methods of simple linear regression and Mann-Kendall statistic etal.The mainly results were as follows:(1)The annual sunshine hours in Dunhuang oasis was increasing at the trend rate of 2.7h/10a and the trend was not evident.(2)In four seasons,the sunshine hours of spring,summer and autumn were increasing.This tendency appeared mainly in spring and the trend rate was 5.5h/10a.However,the tendency in winter was decreasing and the trend rate was-0.8h/10a.(3)The results of Mann-Kendall statistic revealed that the increase of the annual sunshine hour was an abrupt phenomenon and it happened around 1987 in Dunhuang oasis.In spring,the sunshine hour changed abruptly in 1959 and 1989.In summer,the sunshine hour changed abruptly in 1964 and 1994.In autumn,the sunshine hour changed abruptly in 1962 and 1987.In winter,the sunshine hour changed abruptly in 1954 and 1986.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".