Response of winter wheat and cotton to climate warming in Northwest China
Bibliographic record
Abstract
Using surface observation data of Xifeng and Dunhuang agricultural meteorological stations from 1981～2004,the impact of climate warming on winter wheat and cotton growth were investigated.The results showed that minimum temperature increase in spring made the turning green date of wheat and sowing date of cotton advanced significantly.The late maximum temperature increase made maturing date of winter wheat advanced and minimum temperature warming made the growth stopping date of cotton delayed.The shortening of the period over wintering to turning green and milky to maturity was significantly correlated with the minimum temperature and maximum temperature of corresponding stage respectively,but the prolonging of the period of turning green to jointing and blossom to milky was correlated with the minimum temperature of corresponding stage.For cotton,sowing to five-leaf stage was shortened with the increase of minimum temperature,and the days of flowering to boll-opening had no changes.The prolonging of the period five-leaf to budding,boll-opening to growth stopping and the whole growth stages was correlated with the minimum temperature of corresponding stage.Evidently,the warming during the growth periods especially in October had a positive effect on cotton production,but had a negative effect on winter wheat production.The minimum temperature during over wintering stages had correlation with the yield of winter wheat significantly,but the maximum temperature of return green to heading and milky to mature were significantly of negative correlation with yield of winter wheat.1000-grain weight of winter wheat started to drop when the average maximum temperature of June reached over 24℃.Cotton yield was significantly correlated with the average minimum temperature before flowering,and the yield before frost was significantly correlated with the lowest temperature of October.
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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".