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Record W2172197475 · doi:10.5539/cis.v4n2p132

Service Oriented Application in Agent Based Virtual Knowledge Community

2011· article· en· W2172197475 on OpenAlexvenueno aff
L. O. Yusuf, Olusegun Folorunso, A. T. Akinwale, I. A. Adejumobi

Bibliographic record

VenueComputer and Information Science · 2011
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceVirtual communityKnowledge managementCyberspaceServiceability (structure)Knowledge sharingThe InternetService (business)Construct (python library)ArchitectureWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

With the availability of the Internet, virtual communities are proliferating at an unprecedented rate. In-depth understanding of virtual community dynamics can help us to address critical organizational and information systems issues such as communities-of-practice, virtual collaboration, and knowledge management. The biggest challenge in fostering a virtual community is the supply of knowledge through services and the willingness to share knowledge with other members. This paper integrates the Service Oriented Architecture and Agent Based Theory to construct a Reinforced Concrete design (RCD) model for Reinforced Concrete Analysts and Designers in virtual communities. The aim of this paper is to elucidate the sharing of knowledge in virtual community from the perspective of RCD serviceability service. Results confirm that RC Designers will share knowledge; if their perceive benefit exceed the cost of their sharing behaviour. This study is useful for the developers of Service oriented Applications for virtual communities to insight into knowledge sharing in cyberspace for RCD.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.018
GPT teacher head0.217
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2011
Admission routes1
Has abstractyes

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