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Record W1487943147

Understanding the Impact of Emerging Technologies on Process Optimization: The Case of RFID Technology

2008· article· en· W1487943147 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

VenueResearch Online (University of Wollongong) · 2008
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsEnablingSupply chainProcess (computing)VisibilityComputer scienceProcess managementBusiness processRisk analysis (engineering)Information technologySystems engineeringBusinessEngineeringWork in processMarketing
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the case of one supply chain in the electricity sector where RFID technology integrated with firm’s information systems acts as an enabler of process optimization. Using a business process approach and laboratory simulation, we explain how the implementation of RFID technology can increase the visibility of information at various layers of the supply chain, allowing members to gather precise information on real demand and improve replenishment processes. On the other hand, while RFID technology has the potential to automate some processes, human intervention is still required. Therefore, use case scenarios and sensitivity analysis should be carefully considered when selecting the proper design (architecture options) for the virtual and hardware components of RFID systems. The choice of the appropriate configuration needs to be integrated in the firm’s strategies and supply chain partner’s vision.

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 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: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.116
GPT teacher head0.353
Teacher spread0.238 · 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