BRAZIL-CANADA: COOPERATION IN NATURAL SCIENCES, MATHEMATICS AND ENGINEERING: PRESENT SCENARIO AND PERSPECTIVES IN THE FEDERAL UNIVERSITY OF BAHIA.
Bibliographic record
Abstract
A cooperação internacional Brasil-Canadá para pesquisa científica em Ciências Naturais, Matemática e Engenharia foi o tema da nossa mesa-redonda no IX Congresso Internacional da Associação Brasileira de Estudos Canadenses (ABECAN). Apresentamos o quadro atual da cooperação em pesquisa científica nessas áreas, na Universidade Federal da Bahia (UFBA) com o objetivo de desenvolver um programa institucional mais sistemático, com a ajuda da Assessoria para Relações Internacionais da UFBA, a fim de aumentar o intercâmbio tanto entre docentes, quanto entre alunos.Abstract: The international cooperation Brazil-Canada for Scientific Research in Natural Sciences, Mathematics and Engineering was the subject of our round table in IX International Congress of Associação Brasileira de Estudos Canadenses (ABECAN). We present the current scenario of scientific research collaboration on those areas at Federal University of Bahia (Universidade Federal da Bahia – UFBA) with the aim of developing a more systematic institutional program with the help of office for International Affairs of UFBA in order to increase both staff faculty and student exchange.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".