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Record W4312831283 · doi:10.1016/j.ifacol.2022.09.599

An overview on olive oil waste valorization scenarios: Life Cycle Approach

2022· article· en· W4312831283 on OpenAlex

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

VenueIFAC-PapersOnLine · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsOlive oilEnvironmental scienceLife-cycle assessmentAgricultureMediterranean BasinWaste managementMediterranean climateProduction (economics)EngineeringGeographyEconomics

Abstract

fetched live from OpenAlex

The olive industry finds significant growth in the Mediterranean basin where olive oil is produced in massive quantities, in a short time. The olive oil processing chain generates a significant quantity of solid and liquid wastes. This waste can cause significant environmental problems in the Mediterranean area. This study is focused on the identification of different recovery scenarios of wastes resulting from the transformation of olive oil in a life cycle approach. Particular attention has been paid to the three main phases of the olive oil life cycle (agricultural phase, production phase and packaging phase). The results can help decision-makers choose the best recovery scenario to reduce environmental impacts by closing waste loops.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.257
Teacher spread0.223 · 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