A comparative study of world outputs and scientific cooperation in the field of biomedical engineering in the Science Citation Index
Bibliographic record
Abstract
Introduction: Due to it’s close relationship with the health care and biomedical engineering position in society and Iran,s Position in the world in this field of science, This study compares the world scientific outputs and scientific cooperation in biomedical engineering in the Science Citation Index, between the years 2002-2011. Methods: Research method is analytical in which scientometric indicators in analysis of co-authorship are used. Research society consisted of 12044 research and academic outputs in biomedical engineering which are indexed in the Science Citation Index during 2002 - 2011. To extract data, we used from version 5/7 Web of Science database and counting and data analysis was performed using Excel software. Results: America (4427), China (990), Germany (869), Canada (818) and England (754), held the most biomedical engineering outputs. The most sub-subject area belonged to materials science (5896), biophysics (1904), and sport science (863).The trend for top subject areas was the cooperation of more than four authors. America (1207), Germany (484), England (478), China (341), and Canada (335), had the most share of cooperation, in scientific documents of biomedical engineering. Elsevier, Wiley-liss, Springer and IEEE were the most active publishers. Top world authors were from America, Portugal, and the Netherlands. The documents with 4 (2268) and 3 authors (2190) exceeded other co-authored documents. Top world research centers consisted of: Calliff System University (America), Montreal University (Canada), Harvard University (America) and Toronto University (Canada). From among 90 countries, Iran (55 records) holds 28th world rank and the third rank in South West Asian countries. Conclusion: No significant relationship was found between the number of co-authors, number of scientific works of the authors and citation absorption. The countries had the more collaboration with other countries were the most productive ones. So there were the direct relationship between the scientific collaborations and the rate of scientific outputs. For the reason that biomedical engineering has the interdisciplinary nature itself, numerious scientific groups specialists are required and the rate of scientific collaborations of this field is daily exceeding. Finally, it may be asserted that the growth of team cooperation and products of researchers of biomedical engineering in the world is ascending and Scientific ideals of our country, seriously require professionals and the government supports and programs. Keywords: Databases; Biomedical Engineering; Cooperative Behavior; Output; Web of Science.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".