Distributed network management for coalition deployments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Large heterogeneous networks have traditionally been managed either by an eclectic mixture of specialized software or by integrated but ad-hoc methods. Networks that support coalition deployments must also deal with the limited interoperability and scalability typical of COTS management systems. Coalition exercises during the Joint Warrior Interoperability Demonstration (JWID99-R) provide a reference for the technical requirements of coalition network management. The distributed network management (DNM) paradigm provides a potential solution by distributing monitoring and control functionality throughout the network to provide improved flexibility scalability, functionality, and federated control. This paper reviews the network management portion of the AUSCANNZUKUS maritime contribution to the JWID99-R Coalition Wide Area Network, and gives an overview of three approaches to DNM that offer potential solutions for managing such a network. Initial work on a CORBA-SNMP based coalition network management system is described.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it