MétaCan
Menu
Back to cohort
Record W1603730794

Bridging local and wide area networks for overlay distributed file systems

2005· article· en· W1603730794 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceScalabilityFile systemNetwork File SystemOverlay networkDistributed computingSelf-certifying File SystemOperating systemComputer networkDistributed File SystemMetadataBridging (networking)Software deploymentNamespaceSupercomputerSSH File Transfer ProtocolThe Internet
DOInot available

Abstract

fetched live from OpenAlex

In metacomputing and grid computing, a computa-tional job may execute on a node that is geographically far away from its data files. In such a situation, some of the issues to be resolved are: First, how can the job access its data? Second, how can the high latency and low bandwidth bottlenecks of typical wide-area networks (WANs) be tolerated? Third, how can the deployment of distributed file systems be made easier? The Trellis Network File System (Trellis NFS) uses a simple, global namespace to provide basic remote data access. Data from any node accessible by Secure Copy can be opened like a file. Aggressive caching strategies for file data and metadata can greatly improve perfor-mance across WANs. And, by using a bridging strat-egy between the well-known Network File System (NFS) and wide-area protocols, the deployment is greatly sim-plified.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.217
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it