International cooperation of Brazilian research engineers: Patterns of collaboration based on a survey of the literature
Bibliographic record
Abstract
In recent years, engineering research has become global and collaborative. In this paper we analyzed the engineering research productivity of Brazil, one of the countries showing significant economic growth in the first decade of the twenty-first century. We have used the Science Citation Index of Web of Science to find out the patterns of research between Brazil and seven Latin American countries (Argentina, Chile, Colombia, Peru, Uruguay, and Venezuela); and between Brazil and countries of the major industrial democracies or G8 group: France, United States, United Kingdom, Russia, Germany, Japan, Italy and Canada. This survey of the literature of engineering clearly demonstrates the utility of well-designed bibliographic databases like the Web of Science; they can be very effective tools for identifying interesting research trends. Finally, conducting research jointly also presumes a place in a strategic network of nations, institutions or organizations able to take a regional or inter-regional role under common interests. Therefore, it is important to understand the geography of scientific and technical cooperations.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.023 | 0.044 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".