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Record W2125965147 · doi:10.1109/edoc.2008.19

Facebook Meets the Virtualized Enterprise

2008· article· en· W2125965147 on OpenAlexaff
Roger Curry, Cameron Kiddle, Nayden Markatchev, Rob Simmonds, Tingxi Tan, Martin Arlitt, Bruce J. Walker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCloud computingComputer scienceWorld Wide WebScalabilityThe InternetDatabaseOperating system

Abstract

fetched live from OpenAlex

ldquoWeb 2.0rdquo and ldquocloud computingrdquo are revolutionizing the way IT infrastructure is accessed and managed. Web 2.0 technologies such as blogs, wikis and social networking platforms provide Internet users with easier mechanisms to produce Web content and to interact with each other. Cloud computing technologies are aimed at running applications as services over the Internet on a scalable infrastructure. In this paper we explore the advantages of using Web 2.0 and cloud computing technologies in an enterprise setting to provide employees with a comprehensive and transparent environment for utilizing applications. To demonstrate the effectiveness of this approach we have developed an environment that uses a social networking platform to provide access to a legacy application. The application is hosted on an internal cloud computing infrastructure that adapts dynamically to user demands. Initial feedback suggests this approach provides an improved user experience while simplifying management and increasing effective utilization of the underlying IT resources.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.102
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0100.011
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1020.022

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 head0.056
GPT teacher head0.309
Teacher spread0.253 · 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
GenreEmpirical

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

Citations27
Published2008
Admission routes1
Has abstractyes

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Same topicKnowledge Management and SharingFrench-language works237,207