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Record W2054206499 · doi:10.1504/ijnvo.2004.005135

Agent facilitated integration of distributed PDM systems

2004· article· en· W2054206499 on OpenAlexaff
Yinsheng Li, Weiming Shen, Hamada Ghenniwa

Bibliographic record

VenueInternational Journal of Networking and Virtual Organisations · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsWestern UniversityNational Research Council Canada
Fundersnot available
KeywordsProduct data managementWorkflowWorkspaceComputer scienceDomain (mathematical analysis)System integrationNew product developmentSystems engineeringMulti-agent systemWorkflow management systemSoftware engineeringDistributed computingProcess managementKnowledge managementProduct lifecycleDatabaseEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper analyses challenges in integrating distributed and heterogeneous PDM systems in a virtual enterprise-like environment, and introduces multi-agent solutions for the integration. With interactive and communicative agents as community and domain professional services, a set of infrastructure and facilities, which support secure distributed management of product documents, workflows and engineering knowledge, have been proposed and described in detail. With this paradigm, distributed PDM systems perform as a virtual unified product development platform, engineers are allowed to collaborate with each other as conveniently as in a single workspace. Considering standardised multi-agents and fundamental product data managed by PDM systems, the proposed paradigm is prospective in combining with higher-end e-business and growing into a virtual-enterprise level integrated system.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.252
Teacher spread0.230 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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