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Record W4408432432 · doi:10.1590/0001-3765202520240496

The “Conhecimento Brasil” Program neglects the structural problems of Brazilian science and fails to offer a solution to the brain drain

2025· letter· pt· W4408432432 on OpenAlexaff
Bruno Eleres Soares, Arthur L. Moura, VANBASTEN N. DE ARAÚJO, Nathália Helena Azevedo, Ana Christina da Costa Cardoso, Maíra R. Cardoso, Gilberto Santana Carvalho, Arildo S. Dias, Daniela de Angeli Dutra, Elvira D’Bastiani, Ana Clara Sampaio Franco, Luísa Genes, Thiago Gonçalves‐Souza, Piatã Marques, Roberta da Silva Medina, Cristiano B. Moura, Raquel Negrão, Erico A. Oliveira Pereira, Guilherme Oyarzabal, Roberta Silveira Pamplona, Ualerson Iran Peixoto, João Pedro de Jesus Pereira, Pedro Henrique Pezzi, Andressa da Silva Reis, Vinícius Cardoso Reis, Érika Garcez da Rocha, Janaína de Andrade Serrano, Iolanda Ramalho da Silva, Carolina de Barros Vidor

Bibliographic record

VenueAnais da Academia Brasileira de Ciências · 2025
Typeletter
Languagept
FieldSocial Sciences
TopicScience and Science Education
Canadian institutionsUniversity of SaskatchewanSimon Fraser UniversityThe Scarborough HospitalYork UniversityUniversity of TorontoMcGill UniversityUniversity of Regina
Fundersnot available
KeywordsBrain drainEngineering ethicsEpistemologyPhilosophyEngineeringEconomicsEconomic growth

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.991
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.028
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0090.007
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0490.059
Insufficient payload (model declined to judge)0.0080.003

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.

Opus teacher head0.040
GPT teacher head0.361
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractno

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