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Record W4405920511 · doi:10.1504/ijplm.2024.143532

Towards sustainable olive oil production: a systematic review of waste management strategies

2024· review· en· W4405920511 on OpenAlex
Mohamed Amir Keskes, Rémy Houssin, Diala Dhouib, Alaeddine Zouari, Jean Claude Renaud

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Product Lifecycle Management · 2024
Typereview
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsÉcole de Technologie SupérieureHôpital Notre-Dame
Fundersnot available
KeywordsProduction (economics)Cleaner productionWaste managementOlive oilSustainable productionEnvironmental scienceBusinessEnvironmental planningEngineeringMunicipal solid wasteEconomicsChemistry

Abstract

fetched live from OpenAlex

The production of olive oil in Mediterranean regions has a considerable negative impact on the environment due to the high production volume and short time frame. However, by applying the principles of the circular economy (CE), various waste management strategies can be identified for the olive oil supply chain. To assess the environmental impact of these waste management strategies, life cycle assessment (LCA) can be utilised. This study presents a systematic review of scientific LCA studies that examine the various wastes generated from the olive oil transformation process and different waste recovery scenarios in the agriculture, production, and packaging phases. We sourced 56 research papers from Web of Science, ScienceDirect, and Scopus, and surveyed them to identify the most commonly used valorisation scenarios and impact categories. Our results can inform decision-makers in selecting the most effective waste management strategies that can reduce environmental impacts by closing the waste loop.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.236
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.349
Teacher spread0.323 · 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