FRAGILIDADES DO COMBATE À LAVAGEM DE DINHEIRO NAS REGIÕES DE FRONTEIRA
Bibliographic record
Abstract
Lavagem de dinheiro, evasão de divisas, descaminho, regiões de fronteira são palavras que se podem associar, facilmente, ao artigo a seguir. Busca-se entender as possíveis fragilidades no combate à lavagem de dinheiro, em especial do ponto de vista de instituições financeira de fronteiras. Analisa-se a importância do colaborador e um paralelo com as novas operadoras de mercado financeiro, as fintechs. Utiliza-se uma metodologia de pesquisa bibliográfica, análises de cenários e ferramentas de combate, além da atualização com a nova circular do Banco Central (BACEN), em que são explícitos direcionamentos para agências de localização de risco, fronteiras. Ao final, concluímos com a necessidade de uma presença nas regiões de fronteiras, de forma intensa, com tecnologia, com atuação pontual de colaboradores.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.011 |
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; both teacher heads agree on what is shown here.
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".