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Record W2913652934 · doi:10.5539/jsd.v12n1p55

Sustainability Indicators for Biobased Product Manufacturing: A Systematic Review

2019· review· en· W2913652934 on OpenAlexvenueno aff
K. Kooduvalli, Bhavna Sharma, Erin Webb, Uday Vaidya, Soydan Ozcan

Bibliographic record

VenueJournal of Sustainable Development · 2019
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsnot available
FundersOak Ridge National LaboratoryUT-BattelleBattelleU.S. Department of Energy
KeywordsSustainabilityProduct (mathematics)Systematic reviewSupply chainBusinessAgricultureManufacturing sectorEnvironmental economicsEnvironmental resource managementEconomicsMarketingMEDLINEEcology

Abstract

fetched live from OpenAlex

Indicators are effective decision-supporting tools to assess and evaluate progress toward sustainability for a given system. This paper reviews the literature on the four pillars of sustainability (environmental, economic, technical, and social) and relevant indicators used in the agricultural, manufacturing, and materials sectors to determine a framework for manufacturing biobased products as only individual sectors have been studied in detail. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) methodology is used to select 40 papers for review in this study. This paper suggests 22 categories encompassing 33 core measurable indicators with respective units for biobased manufacturing sectors to determine the sustainability of an end product while holistically understanding the standpoint of biomaterial industries in assessing a sustainable supply chain.

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)0.014
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.047
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0260.020
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0020.001
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 head0.025
GPT teacher head0.281
Teacher spread0.256 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2019
Admission routes1
Has abstractyes

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