A bibliometric analysis of Medical Papers published by Huai'an First People's Hospital during 2002-2011
Bibliographic record
Abstract
Object Bibliometrically analyzed are the medical papers of Huai'an First People's Hospital from 2002 to 2011 on CBMdisc.Methods Our own program and excel 2007 are used to statistically analyze the annual change,distribution of periodicals,authors,department,fund papers as well as citations of medical papers published by staff of Huai'an First Hospital in 10 years.Results 1935 Chinese papers were published from 2002 to 2011.However,Huai'an First Hospital began to publish SCI papers since 2009,a total of 24,accounting for only 1.23％ of the total number of papers in English.According to Price's law,there are 136 core authors who published nearly half of Chinese papers(955).The two bright academic leaders Li Yufeng and Yu Liang in Hematology swept a quarter of SCI papers.All the 136 core authors and two academic leaders are well deserved scientific research backbones of our hospital.Chinese papers' total cited rate is 47.29 ％,cited frequency 2.99 times.SCI papers' cited rate is 75％,cited frequency 2.83 times.Conclusions The amount of papers,amount of papers published on core journals and SCI papers volume increased year by year.But there is a great disparity of proportion between the amount of papers published on domestic journals and SCI papers volume.It is necessary to improve papers quality. Key words: Medical papers; Bibliometrics; hospital
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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 | 0.032 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.699 | 0.896 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.009 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 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; 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".