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Record W2131528018 · doi:10.1109/icsmc.2008.4811841

Development of an intelligent agent-based mobile phone supply chain simulation system

2008· article· en· W2131528018 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

VenueConference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSupply chainComputer scienceSupply chain managementMobile phoneProduct (mathematics)Component (thermodynamics)Intelligent agentMulti-agent systemLayer (electronics)Manufacturing engineeringBusinessEngineeringTelecommunicationsArtificial intelligenceMarketing

Abstract

fetched live from OpenAlex

An intelligent agent-based mobile phone supply chain simulation system is developed, in which a business entity or customer is represented by an intelligent agent. The proposed simulation system has six layers - raw material providers, component manufacturers, product assemblers, product holders, retailers, and final customers. There are two agents in each layer. An agent has a number of engines to implement various functions of the agent. This system can simulate many activities of a business in a supply chain either automatically or manually. The system can be used to study and simulate supply chain management technologies and methodologies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.058
GPT teacher head0.273
Teacher spread0.215 · 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