Articulated private networks in UCLP
Bibliographic record
Abstract
Purpose – The purpose of this paper is to illustrate the advantages of using the UCLP software for network operators, advanced and regular end users in the research networking community. Design/methodology/approach – This paper provides an example of the deployment of UCLP in the GÉANT2/National Research and Education Networks (NRENs) scenario, and compares how network operators, advanced users and regular end users would do their work, with and without UCLP. Findings – The paper provides high‐level technical information about UCLP as well as depicting the drivers for its use in the European research networking community. Research limitations/implications – This paper does not explain the details of the deployment of the software in the GÉANT2/National Research and Education Networks (NRENs) scenario, it just explains the benefits that the deployment of the software would provide. If the deployment was to be done today, some improvements to UCLP should be done, as well as support for more equipment vendors should be added. Practical implications – UCLP could provide more flexibility to the e‐science community if it was deployed over the European research networking infrastructure, because it would isolate network users from each other while providing them an unprecedented degree of control over the network. Originality/value – Nowadays, several control/management solutions for networks exist, but none that is capable of partitioning a physical network into slices and handoff its management to the users, like UCLP does. This is the first UCLP paper that studies a hypothetical deployment of UCLP in the European research networking scenario, and evaluates the drivers and implications of such a deployment.
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 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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".