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Record W2075186415 · doi:10.14419/ijet.v4i1.3813

Lifecycle assessment of a stapling machine

2014· article· en· W2075186415 on OpenAlexaff
Israel Dunmade

Bibliographic record

VenueInternational Journal of Engineering & Technology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsMount Royal University
Fundersnot available
KeywordsLife-cycle assessmentEnvironmental impact assessmentEnvironmental scienceEutrophicationBusinessProduct (mathematics)Environmental resource managementOperations managementEngineeringProduction (economics)

Abstract

fetched live from OpenAlex

A stapler is a mechanical device used to join two or more sheets of paper together by driving a thin metal staple through the sheets. They are widely used in schools, offices, business, government and homes. The anticipated large quantity of waste that is disposed of annually present great risk of environmental pollution and opportunities for economically viable resource recycling. This study evaluates potential environmental impacts of a Stapling machine and its end-of-life management opportunities. Environmental lifecycle assessment (LCA) process was used for the evaluation. The assessment was implemented with the aid of SimaPro software version 7.3.3.Results of the analyses revealed that climate change and eutrophication are the significant potential environmental impacts. Each Stapler has 1.265130 kg CO2-eq in Global Warming Potential and 0.113067 max kg O2-eq as its Eutrophication Potential. Further examination also showed that most of the impacts are from material selection, product distribution, and end-of-life management of the stapling machine. This study provides insights on potential environmental impacts of stapling machines and potential opportunities for improvements in their end-of-life management.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.003
GPT teacher head0.247
Teacher spread0.244 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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