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Record W3151719700 · doi:10.5267/j.uscm.2021.2.008

Optimizing the polymer waste supply chains based on circular economy

2021· article· en· W3151719700 on OpenAlexvenueno aff
Tetyana Skrypko, Nazariy Popadynets, Tetiana Yakhno, Роман Степанович Шулла, Тетяна Власенко, Inna Irtyshcheva, Yevheniia Boiko

Bibliographic record

VenueUncertain Supply Chain Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainability and Innovation in Business
Canadian institutionsnot available
Fundersnot available
KeywordsCircular economySupply chainSortingQuality (philosophy)Production (economics)Industrial organizationBusinessEnvironmental economicsEmpirical researchComputer scienceEconomicsMicroeconomicsMarketing

Abstract

fetched live from OpenAlex

The paper shows the results of an empirical study on the optimization of polymer waste supply chains based on the circular economy in Ukraine. The research shows that the main links in the activity should be harmonized for quality and quick optimization of polymer waste supply chains, including the processes of collecting, sorting, treatment, processing, and recycling of resources for maintaining the quality by total cost reduction. The research argues that the circular economy that stipulates the easy processing, recycling, disassembling, and restoring of products replaced the traditional linear model “take, produce, and throw out” that has dominated the economy by now. The study shows that the transformation of supply chains in production ecosystems forms competitive advantages at the enterprises that allow them to be more productive through efficient use of resources.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.219
Teacher spread0.205 · 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 designSimulation or modeling
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

Citations9
Published2021
Admission routes1
Has abstractyes

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