Statistics and Analysis for SCI Papers Published by Northwest A&F University
Bibliographic record
Abstract
The SCI-E(Science Citation Index-expanded) papers published by Northwest AF University since its founding in 1999 were counted and analyzed.The results indicated that 905 papers in all have been included by SCI-E database up to December of 2008,the number of papers included by SCI-E increased year by year;in which 256 papers were included by SCI-E in 2008;it was the highest record in the past ten years.The papers published in journals were 781,which were 86.4% in total,and they were mainly distributed in 320 SCI-E source journals.The influence factors of 8 foreign journals were not high ranged from 0.691-2.532,in which many papers were published;In the past decade,over one thousand authors published only one or two SCI papers,at the same time,a few authors were very fruitful and published many even near one hundred papers;the above SCI-E papers mainly belonged to low-citation range(423 papers) and zero-citation-range(462 papers),the high-citation papers mainly published in international journals,and low-citation papers were mainly published in Chinese journals.The papers dealt with 85 disciplines,among them 743 papers were published the ranking top 10 disciplines,which were occupied by 81.74% in total,they basically were key disciplines of our University.Some papers were written thorough extensive cooperation with 34 advanced countries and regions in the fields of science and technology such as US,Britain,Canada,Germany and Japan,as well as other universities and research institutions at home.The collaborated papers were 337.In conclusion,our university lies in the good development period;it can be expected that more and more cooperated SCI-E papers will be published in the future with the joint efforts.
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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 | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.039 | 0.045 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".