Bibliographic guidance workshops: resources of research portals and information and documentation standards as extension courses
Bibliographic record
Abstract
Training the university community in the use of technical standards for information and documentation is a common practice aimed at ensuring that academic production follows and applies the standards indicated in these norms. This standardization helps maintain formal presentation and proper composition of documents within the university environment while also contributing to the scientific communication process. Since 2005, the Central Library of UEPG has offered training sessions for using the CAPES Portal, conducting database searches, and providing bibliographic orientation workshops for applying technical standards such as the Brazilian Association of Technical Standards (ABNT), APA, and Vancouver style. The training primarily addresses three key aspects: formal presentation – NBR 14724, citations – NBR 10520, and references – NBR 6023. This study highlights the metrics achieved between 2019 and 2023 across various courses that requested and participated in the trainings, noting fluctuations during critical years of the COVID-19 pandemic. Participation decreased in the first year (2020) but increased in the second year (2021) due to the virtual format of the sessions. The demand for these trainings is significant, responding to the needs and interests of undergraduate and graduate programs, and contributes to the proper composition of their scientific productions.
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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 | 0.029 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.020 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.127 | 0.053 |
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".