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Record W2051670689 · doi:10.4271/2014-01-2232

A Conceptual Framework for Value Chain Analysis of End of Life Aircraft Treatment in the Context of Sustainable Development

2014· article· en· W2051670689 on OpenAlexaff
Samira Keivanpour, Christian Mascle, Daoud Aı̈t-Kadi

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsPolytechnique MontréalUniversité Laval
Fundersnot available
KeywordsContext (archaeology)Sustainable developmentValue (mathematics)Chain (unit)Value chainComputer scienceProcess managementBusinessSupply chainMarketingGeographyPolitical science

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The End of Life phase of Aircraft is a relatively complex phase in life cycle of this product. The retired Aircrafts need to be parked in certain conditions. Some valuable parts are disassembled and the rest of them are dismantled. Materials are separated and upgraded, waste is burned or deserted and toxic materials restrained or incinerated. All of these activities should be performed in an ecologically right manner; however, collectively produced added values for all stakeholders need to be considered. This paper aims to provide a conceptual framework for value chain analysis of Aircraft recycling process in the context of sustainable development. The value chain related to recycling aircraft at the end of life was chosen to generate an in-depth analysis of the value chain, considering environmental and socio-economic concerns. The value chain framework for recycling of fleets is identified. The key processes with environmental and social impacts are determined. The decision making process along the value chain and the policy framework including codes, regulations and standards are addressed. Finally, the proposed approach with providing a basis for evaluation of effectiveness, efficiency and stability across the value chain aids decision makers to design a sustainable framework for End of Life aircrafts treatment.</div></div>

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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 teacher head, not a consensus.

Study designObservational
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

Citations7
Published2014
Admission routes1
Has abstractyes

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