China experiencing the recent warming hiatus
Bibliographic record
Abstract
Abstract Based on the homogenized data set, we analyze changes in mean temperature and some extreme temperature indices over China since 1961 and especially during the recent warming hiatus period (1998–2012) in a global average context. The result shows that the decrease of annual mean maximum has contributed most to the decreases in overall mean temperature and in diurnal temperature range (DTR) during the warming hiatus period. In most parts of China except the southwest, the summer mean maximum temperature ( T xS ) shows the largest increase, while the winter mean minimum temperature ( T nW ) indicates slight cooling trends. These changes have augmented the seasonal cycle and increased the likelihood of extreme warm and cold events. Further analyses reveal that the increases in T xS are significantly correlated with concurrent increases in solar radiation. In southwest China, the annual mean temperature, T xS , T nW , and DTR increased during 1998–2012, possibly related to increased dryness in this region during the hiatus period.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".