Expresión escrita y trabajos científicos
Bibliographic record
Abstract
Las normas de la American Psychological Associution (APA) y las normas de Vancouver son las más reconocidas por la comunidad científica internacional. En este artículo nos centramos en las normas de la APA ya que actualmente son las más utilizadas y sirven de guía a todos los investigadores para presentar sus escritos, si pertenecen a las más variadas áreas de conocimiento. Los investigadores de las ciencias médicas y de la salud se rigen, frecuentemente, por las normas de Vancouver. Se exponen las reglas más comunes y las que más frecuentemente se infringen en los trabajos escritos, completándolas con algunas sugerencias para el uso correcto de la lengua castellana. Este artículo no exime, al autor de cualquier trabajo científico, de leer el Manual de estilo de publicaciones de la APA o de conocer, al menos en su esencia, las normas de Vancouver.
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 | 0.066 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.022 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".