The analysis of the latest statistical results for China journals indexed by SCI(E),SSCI and A&HCI databases
Bibliographic record
Abstract
Aim To confirm the exact number of China journals which were indexed by SCIE,SSCI and AHCI databases in Web of Science.Methods The words such as China,Taiwan,Hong Kong and Macau are used as retrieval words in the Web of Science platform for retrieval China journals.The retrieval results are analyzed by Analyze Results,the results are sorted by Source Titles to identify top 500 journals of Chinese authors' published papers and to confirm whether their sponsors belong to China.Results 207 China journals indexed by Web of Science are published in 22 different regions containing provinces,municipalities,autonomous regions and special administrative regions in China.148 journals are published in mainland China,39 journals in Taiwan and 20 journals in Hong Kong.33 journals are included in SCI database,188 journals in SCIE database,16 journals in SSCI database and nine journals in AHCI database.In 207 journals,the university journals of science and technology account for about a quarter.Conclusion Though more than 200 China journals are indexed by SCIE,SSCI and AHCI databases in Web of Science,the journals with high impact factor are few(with considering the differences in disciplines),95% of the selected journals with impact factor are less 2.0 in 2010.Therefore our future direction should be to improve the quality of the journals,and to extend the international influence.
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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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".