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A FRAMEWORK FOR DEVELOPING IMPLEMENTATION STRATEGIES FOR A RADIO FREQUENCY IDENTIFICATION (RFID) SYSTEM IN A DISTRIBUTION CENTER ENVIRONMENT

2009· article· en· W2071105444 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

VenueJournal of Business Logistics · 2009
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsPalletInteroperabilityRadio-frequency identificationSupply chainBarcodeComputer scienceContext (archaeology)Identification (biology)Process managementSupply chain managementBusinessMarketingWorld Wide WebComputer security

Abstract

fetched live from OpenAlex

The costs and benefits of RFID adoption by supply chains have been a matter of much debate. As a result, researchers are finding a greenfield opportunity to examine how organizations might make use of the technology in a supply chain context. This paper attempts to further explore the potential contribution and limitations of RFID in a warehouse setting in two ways. First, it discusses the issues surrounding pallet‐level tagging and case‐level tagging by developing a decision making framework. Second, insights from the framework are used to define an object‐oriented modeling framework that facilitates warehouse simulation of the RFID vs. barcode interoperability. This simulation is used to explore some of the cost/performance tradeoffs associated with six implementation strategies. Important cost tradeoffs are reported for the different strategies, and the statistical significance of the differences are evaluated.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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