Temporal and spatial variations in haze research: a bibliometric analysis
Bibliographic record
Abstract
This study examines haze research literature published between 1998 and 2018 using bibliometric methods based on databases of the Science Citation Index, the Social Science Citation Index, the Conference Proceedings Citation Index – Science, and the Conference Proceedings Citation Index – Social Science and Humanities. Of 7911 retrieved publications, 92% are journal articles. From the temporal variation, changes in the key words of these studies between 1998 and 2018 showed the dynamic evolution of categories of haze research. Scientists have studied haze from the initial suspended particles to the characteristics, components, sources, influence factors, and hazards of the particles and finally established a mature research system. The spatial analysis revealed hot spot regions and international cooperation. The results showed the United States and China were the two countries with the most articles. Spatial proximity provided convenience in country cooperation. The modular analysis showed the United States and China were the two core countries in collaboration with other countries/regions and played key roles in international collaboration. In addition, haze events are trans-boundary issues urging cooperation among countries. These findings are useful for the future endeavor of haze related academic research.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.031 |
| 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) | 0.006 | 0.005 |
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; both teacher heads agree on what is shown here.
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".