Aplicación móvil para la organización de referencias bibliográficas por las normas de Vancouver
Bibliographic record
Abstract
Introducción: frecuentemente se identifican dificultades en la organización de las referencias bibliográficas por las Normas de Vancouver. Objetivo: desarrollar la aplicación para dispositivos móviles Normas de Vancouver-APK para la organización de las referencias bibliográficas. Método: se utilizó HTML5, CSS3, JavaScript, Java, Visual Studio Code, Android Studio y adobe Photoshop. Resultados: en este trabajo se muestra el prototipo de aplicación Normas de Vancouver-APK para dispositivos móviles, sus ventajas, la dirección electrónica donde se puede descargar, y el manual de usuario para generar y recuperar las referencias bibliográficas a través del llenado del formulario según el tipo de documento utilizado. Conclusiones: la aplicación contribuye a la organización de las referencias bibliográficas por las Normas de Vancouver de una manera más fácil, limitando la complejidad para el que lo redacta. Palabras clave: aplicaciones móviles; normas de Vancouver; organización de referencias bibliográficas. ABSTRACT Introduction: Difficulties are frequently identified in the organization of bibliographic references by the Vancouver Standards. Objective: To develop the Vancouver Rules-APK application for mobile devices for the organization of bibliographic references. Method: HTML5, CSS3, JavaScript, Java, Visual Studio Code, Android Studio and Adobe Photoshop were used for its construction. Results: This paper shows the Vancouver Standards-APK application prototype for mobile devices, its advantages, the electronic address where it can be downloaded, and the user manual to generate and retrieve bibliographic references by filling in the form according to the type of document used. Conclusions: The application contributes to the organization of the bibliographic references by the Vancouver Standards in an easier way for the one who writes it. Keywords: mobile applications; Vancouver Standards; organization of bibliographic references.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".