Analysis of papers published in Chinese Journal of Optometry & Ophthalmology from 1999 to 2008
Bibliographic record
Abstract
Objective To evaluate the academic level and quality of Chinese Journal of Optometry Ophthalmology by analyzing the papers published from 1999 to 2008.Methods The papers published in Chinese Journal of Optometry Ophthalmology from 1999 to 2008 were surveyed.The number of papers,the columns,the distribution of papers,the papers with founded projects,the number and job title of authors were analyzed by bibliometrics.Results One thousand one hundred and forty papers covered 11 columns (comprised 10 volumes 46 issues) were published in the past 10 years.The papers came from 30 provinces and Taiwan,Hongkong in China and other countries like American,Canada,Japan.Two hundred and seventy-three papers had the scientific and research foundation (23.9%).Most of the authors got high education came from the universities and hospitals which locate in the developed coastal areas like Zhejiang,Shanghai,Guangdong and Beijing.The average number of authors per paper was 3.4 and the cooperation rate was 89.4%.Conclusion The Chinese Journal of Optometry Ophthalmology has great development in the 10 years with high value and wide influence,but needs more progress.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.064 | 0.075 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".