Diretrizes para apresentação de dissertações e teses da USP: parte IV (Vancouver) 2.ed
Bibliographic record
Abstract
O Sistema Integrado de Bibliotecas da Universidade de São Paulo – SIBi/USP, dentre suas propostas voltadas à padronização dos trabalhos científicos, publica trabalhos no sentido de orientar os alunos de pós-graduação na elaboração de suas teses e dissertações geradas na Universidade. Neste sentido, dando sequência a este trabalho, traz a público a atualização das “Diretrizes para apresentação de dissertações e teses da USP: documento eletrônico e impresso”. Para facilitar a consulta às normas o Grupo responsável pela atualização elaborou o trabalho em quatro partes, cada parte enfocando uma norma específica: Parte I (ABNT – Associação Brasileira de Normas Técnicas), Parte II (APA – American Psychological Association), Parte III (ISO – International Organization for Standardization) e Parte IV (Vancouver). Este documento apresenta a 2ª edição revisada das Diretrizes publicada em 2009, de acordo com a norma Vancouver atualizada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.006 |
| 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; 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".