Evaluación de la infraestructura de red de datos del programa de la Universidad en el Campo (UNICAM) de la UNAN-Managua – FAREM-Matagalpa. Nicaragua. 2017
Bibliographic record
Abstract
This article presents an analysis of the current state of the internet network infrastructure of the Universidad Nacional Autónoma de Nicaragua, Managua (UNAN-Managua) - Facultad Regional Multidisciplinaria de Matagalpa (FAREM-Matagalpa) in the municipalities participating in the "Universidad en el Campo" (UNICAM) program. The current state of the data network was characterized, thus defining the requirements of the services according to the users and according to the ITIL 2011 good practices guide. This research has a quantitative approach with qualitative implications, the research design is non-experimental, explanatory and cross-sectional; we worked with a population of 80 students of the careers offered in four UNICAM sites, where there is network infrastructure; an ICT area manager, a UNICAM program director, two technicians and 16 teachers. For the collection of information, we used techniques such as interviews with the ICT area and UNICAM program directors, support technicians, ITIL-based assessment scales applied with the approval of the Faculty's ICT management, and online surveys directed to students. At the conclusion of the evaluation of the Internet network infrastructure, it is affirmed that users are satisfied, although not satisfied with the service currently provided, that the existence of the network infrastructure is essential for the development of academic activities and that the level of maturity of ITIL processes in these municipalities is 37% of that recommended by the guide, which makes evident the need to strengthen the current services and infrastructure.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".