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Record W4389895439 · doi:10.1080/17477778.2023.2293861

Simulation- optimisation approach to support management of blood components inventory

2023· article· en· W4389895439 on OpenAlex
Virgínia Silva Magalhães, Luiz Ricardo Pinto, Lásara Fabrícia Rodrigues, John T. Blake

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 Simulation · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsCanadian Blood Services
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsEconomic shortageInventory managementComputer scienceSupply chainBlood supplySupply chain managementOperations managementDiscrete event simulationInventory controlBlood managementOperations researchSimulationBusinessBlood lossMedicineEngineeringSurgery

Abstract

fetched live from OpenAlex

Blood supply chains (BSCs) face challenges in managing the production and inventory of blood components. We developed a simulation-optimisation approach to address inventory of blood products in blood supply chains. This approach can determine inventory size and replenishment points for blood products that balances supply and demand, while maintaining acceptable levels of wastage and shortage. A simulation methodology is used to represent the complexities in the inventory management of blood components. An optimisation module, coupled with the simulation, is used to address constraints related to waste, shortages, and inventory levels. The approach was verified and validated using a case study conducted in a blood bank in Brazil managing a supply of Red Blood Cells (RBCs). The approach proved to be suitable for the case analyzed and results suggest that 120 units is adequate to meet the demand for RBCs, while maintaining acceptable levels of shortages and wastages.

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: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.073
GPT teacher head0.301
Teacher spread0.229 · 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