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Record W4308179940 · doi:10.1039/d2ra03253h

Valorization of camelina oil to biobased materials and biofuels for new industrial uses: a review

2022· review· en· W4308179940 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRSC Advances · 2022
Typereview
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsLethbridge CollegeMinistry of Agriculture, Food and Rural AffairsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Agri-Food Innovation AllianceUniversity of ManitobaMinistero dello Sviluppo EconomicoOntario Ministry of Agriculture, Food and Rural AffairsUniversity of WaterlooOntario Ministry of Economic Development, Job Creation and TradeUniversity of TorontoArboraNanoRoyal Society of CanadaAgriculture and Agri-Food CanadaRoyal SocietyMinistry of Agriculture, Food and Rural AffairsArrell Food Institute, University of GuelphUniversity of Guelph
KeywordsCamelinaBiofuelCamelina sativaPulp and paper industryBiochemical engineeringEnvironmental scienceWaste managementChemistryFood scienceEngineeringAgronomyBiologyCrop

Abstract

fetched live from OpenAlex

, generally known as camelina, which has limited use as a food oil and so is currently being explored as a feedstock for various industrial applications in both Europe and North America. Camelina oil is highly unsaturated, making it an ideal potential AGH feedstock for the manufacture of lower carbon footprint, biobased products that reduce our dependency on petroleum resources and thus help to combat climate change. This review presents a brief description of camelina highlighting its composition and its production in comparison with traditional plant oils. The main focus is to summarize recent data on valorization of camelina oil by various chemical means, with specific emphasis on their industrial applications in biofuels, adhesives and coatings, biopolymers and bio-composites, alkyd resins, cosmetics, and agriculture. The review concludes with a discussion on current challenges and future opportunities of camelina oil valorization into various industrial products.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.105
GPT teacher head0.338
Teacher spread0.233 · 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