Cómo redactar un artículo científico para una revista
Bibliographic record
Abstract
espanolEl articulo original o de investigacion es el medio principal para la comunicacion cientifica. Un articulo original es un informe que comunica los resultados de investigaciones, ideas y debates de manera clara, concisa y fidedigna. En el campo de las ciencias de la salud, la estructura de un articulo original sigue el formato llamado IMRD, que hace referencia a sus partes fundamentales: Introduccion, Metodos, Resultados y Discusion. Otras secciones del articulo son: titulo, resumen, agradecimientos y bibliografia. La introduccion describe el tema sobre que se ha realizado la investigacion y el objetivo de la misma; las seccion de metodos describe como se ha llevado a cabo; en la seccion de resultados se presentan los datos (numericos o conceptuales) que se han encontrado; mientras que la discusion permite resaltar el significado de los hallazgos y su relevancia para la disciplina. Existen varios formatos para presentar las referencias bibliograficas en el articulo, algunos de los mas utilizados son: formato Vancouver, APA y Harvard. EnglishResearch papers are the main way for scientific communication. A research paper is a report that informs on the results of a research, ideas and scientific discussion in a clear, brief and reliable way. In healthcare field, articles are usually structured following the IMRD format: Introduction, Methods, Results and Discussion. Title, abstract, acknowledgement and references are others sections of an article. The introduction describes the research problem and the aim; the methods section explains how the research was carried out; data (both numeric and conceptual) are presented in the results section; whereas the discussion allows pointing out the meaning of the findings and its relevance in the field of knowledge. Bibliographic references can be written in several formats, some of the most used are: Vancouver, APA and Harvard.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".