Desarrollo del Front-End de una aplicación web con el framework EXT JS 5
Bibliographic record
Abstract
Este trabajo de fin de grado trata sobre el desarrollo de una aplicación web utilizando uno de los frameworks de JavaScript más potentes del mercado, el EXT JS5. Este ha sido desarrollado por Sencha. \nLa memoria está dividida en 9 capítulos, en los cuales se explican los conocimientos básicos que un desarrollador debe tener para comenzar a utilizar el EXT JS 5; las ventajas y los contras de este framework respecto a otros; una descripción general de cómo desarrollar el Front-End de una aplicación web con EXT JS 5 (se incluye la posibilidad de descargar una aplicación creada por el autor de la memoria para facilitar el aprendizaje del lector); se describe la aplicación que el autor ha desarrollado como proyecto fin de grado. Finalmente, se detalla el presupuesto, diagrama de Gantt y restricciones que el programador ha tenido en cuenta para el desarrollo de la aplicación.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".