Utilización de Zotero como gestor bibliográfico web en estudiantes universitarios
Bibliographic record
Abstract
El presente artículo, tiene como objetivo conocer la utilización del gestor bibliográfico Zotero en los estudiantes que tomaron las cátedras relacionadas a las (Tecnologías de la información y Comunicación) TICs en la Facultad de Salud Pública en los periodos académicos comprendidos entre Marzo – Julio 2013 y Abril – Agosto 2016. Se realizó un estudio descriptivo, mediante la aplicación de una encuesta difundida a través de redes sociales, correos electrónicos. En el análisis estadístico se utilizó la Técnica de Análisis de Datos Textuales (AEDT) para preguntas abiertas. El 88,4% de los encuestados considera de fácil instalación la herramienta en análisis, el buscador Google Académico es el más utilizado con 82,6%, la norma Vancouver lo utilizan el 73,3% de los encuestados. Se reconoce la facilidad de la utilización del complemento Zotero en la gestión bibliográfica por parte de los estudiantes participantes en el estudio.
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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 | 0.012 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".