Cap VII. Redacción científica empleando normas y gestores bibliográficos: revisión documental
Bibliographic record
Abstract
El objetivo del documento es resaltar el uso de los gestores bibliográficos: Mendeley y Zotero partiendo que su uso es cada vez más importante y requerido en los entornos académicos y científicos; además, describir las pautas de escritura científica empleando las normas APA 7ª edición del Manual de Publicación de la Asociación Americana de Psicología y una comparación con las Normas ISO 690 y las Normas Vancouver. La metodología aplicada al estudio, parte de una revisión documental que desarrolló la presentación de pasos y consideraciones a tomar en cuenta para elaborar el contenido de un manuscrito científico con la instalación y uso de los gestores bibliográficos, tablas, figuras, y las referencias de citas. El documento aporta información destinada a estudiantes e investigadores que están iniciando la escritura científica, así como se demuestra estudios con aportes relacionados a la investigación.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.022 |
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".