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Record W2146532238 · doi:10.1145/1352592.1352598

Parallax

2008· article· en· W2146532238 on OpenAlexaff
Dutch T. Meyer, Gitika Aggarwal, Brendan Cully, Geoffrey Lefebvre, Michael J. Feeley, Norman C. Hutchinson, Andrew Warfield

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceStorage virtualizationConverged storageVirtualizationSnapshot (computer storage)Computer data storageArchitectureObject storageCacheTemporal isolation among virtual machinesEmbedded systemOperating systemInformation repositoryComputer hardwareCloud computing

Abstract

fetched live from OpenAlex

Parallax is a distributed storage system that uses virtualization to provide storage facilities specifically for virtual environments. The system employs a novel architecture in which storage features that have traditionally been implemented directly on high-end storage arrays and switches are relocated into a federation of storage VMs, sharing the same physical hosts as the VMs that they serve. This architecture retains the single administrative domain and OS agnosticism achieved by array- and switch-based approaches, while lowering the bar on hardware requirements and facilitating the development of new features. Parallax offers a comprehensive set of storage features including frequent, low-overhead snapshot of virtual disks, the 'gold-mastering' of template images, and the ability to use local disks as a persistent cache to dampen burst demand on networked storage.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0580.021

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 head0.030
GPT teacher head0.247
Teacher spread0.216 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations120
Published2008
Admission routes1
Has abstractyes

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