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Record W2117171251 · doi:10.1109/icsmc.2007.4414189

Design of an intelligent agent-based supply chain simulation system

2007· article· en· W2117171251 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSupply chainSupply chain managementMulti-agent systemIntelligent agentNegotiationProduct (mathematics)Computer scienceService managementComponent (thermodynamics)Information sharingSupply chain risk managementSystems engineeringProcess managementRisk analysis (engineering)BusinessEngineeringMarketingWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

An intelligent agent-based supply chain simulation system is designed, in which a supply chain entity is represented by an agent. There are six layers in this system: raw material providers, component manufacturers, product assemblers, product holders, retailers, and final customers. A detailed agent structure is presented and various functions of the agent are described. Moreover, communication activities among agents are discussed. By using the proposed system, issues in supply chain integration, information sharing among supply chain partners, demand forecasting, supply chain risk management, and automated communication and negotiation, could be simulated and studied.

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.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.041
GPT teacher head0.261
Teacher spread0.220 · 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

Quick stats

Citations12
Published2007
Admission routes1
Has abstractyes

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