Bibliographic record
Abstract
Community operated Metropolitan Area Networks play an increasingly important role in today's society; information and knowledge are key elements of the production and innovation processes, as part of economic and social development.We define community operated metropolitan area networks as those communication infrastructures which span a geographical area of a few square kilometres and extend over all or part of a town or region. Owned and operated by a specific community or an entity that represents it, they aim to offer a set of services of common interest to those communities.In order to enable online services such as eLearning, eSience, eHealth and eGovernment, as well as to promote the establishment of virtual communities and the development of emerging services, communication infrastructures which provide high capacity, availability and performance are essential.Local governments are increasingly encouraged to intervene, both by public opinion and supranational entities such as the European Union. They are expected to deploy and operate metropolitan area networks with the abovementioned characteristics, providing citizens with low-cost communication facilities. Several such fibre optic infrastructures have been implemented in the last few years, not only in Europe but also in Canada, Australia and the United States.This essay analyzes and describes the most relevant technological options concerning the deployment of metropolitan networks; It focuses on their characteristics, advantages and disadvantages in order to present a proposition for the creation of a high-capacity communication infrastructure in the city of Porto.An actual solution has been reached, comprising not only the passive and active components of the network, but also a general approach to the way the different services may be provided, as well as an operational model fitting the specific requirements of the city. This solution is based on the Virtual Private LAN Services Model, implemented over a Multiprotocol Label Switching enabled IP backbone.This work, as well as its conclusions, may be a relevant contribution to the decision making process concerning the subproject "Infra-estrutura Física" (physical infrastructure) coordinated by the University of Porto and which is part of the project "Porto Digital", included in the national initiative "Cidades e Regiões Digitais".
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 | 0.012 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; 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".