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Record W4410050703 · doi:10.63471/tbfli24001

IT in Improving Integrity and Productivity in Supply Chain Management

2024· article· en· W4410050703 on OpenAlexaff
Barna Biswas

Bibliographic record

VenueTransactions on Banking Finance and Leadership Informatics · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsWycliffe College
Fundersnot available
KeywordsProductivitySupply chainBusinessSupply chain managementSupply chain risk managementIntegrity managementEnvironmental scienceNatural resource economicsService managementEnvironmental engineeringEconomics

Abstract

fetched live from OpenAlex

Supply Chain Management is a crucial field that involves the flow of information, materials, and finance within a network of suppliers, manufacturers, distributors, and customers. It has revolutionized the role of management in enhancing supply chain operations and addressing the knowledge-intensive nature of economies. Information Technology has significantly influenced this shift, making new product development more complex and competitive in dynamic market environments. This has led to the need for more accurate knowledge and information to satisfy customers' changing needs. The role of IT in supply chain management is crucial, as it helps manage e-risks and enhance the efficiency and efficacy of supply chain processes. The study examines how technology is changing supply chain management, highlighting its role in enhancing business operations and addressing the ever-changing needs of customers.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0030.004
Scholarly communication0.0130.016
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.003

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 head0.094
GPT teacher head0.271
Teacher spread0.177 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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