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Record W2107308752 · doi:10.1504/eg.2009.024441

Multi-agent based framework for e-government

2009· article· en· W2107308752 on OpenAlexaff
Sehl Mellouli, Faouzi Bouslama

Bibliographic record

VenueElectronic Government an International Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAnticipation (artificial intelligence)Agency (philosophy)Government (linguistics)ArchitectureChristian ministryService (business)Process managementComputer sciencePoint (geometry)Service-oriented architectureBusinessService delivery frameworkKnowledge managementWeb serviceWorld Wide WebMarketingArtificial intelligencePolitical science

Abstract

fetched live from OpenAlex

This paper presents an architecture framework with underlying technologies that are appropriate to design and deploy efficient government services. Service-oriented architecture driven by intelligent multi-agent components is proposed as a solution to achieve governments' goals of citizens focused efficiency, responsiveness and anticipation. Services are clustered into grapes of services related to specific government domains. Citizens have access through a single multichannel entry point and via service grapes to any service provided by a ministry or a public agency. The results of this research enable governments to be aware of innovative technologies that can assist them in better serving their citizens.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.340
Teacher spread0.318 · 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.

Study designTheoretical or conceptual
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

Citations12
Published2009
Admission routes1
Has abstractyes

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