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Plant surface lipid biosynthetic pathways and their utility for metabolic engineering of waxes and hydrocarbon biofuels

2008· article· en· W2120078999 on OpenAlex
Reinhard Jetter, Ljerka Kunst

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

VenueThe Plant Journal · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWaxMetabolic engineeringWax esterAlkaneCuticle (hair)Metabolic pathwayBiofuelBiochemical engineeringHydrocarbonBiologyChemistryGeneBiotechnologyBiochemistryOrganic chemistryEngineeringGenetics

Abstract

fetched live from OpenAlex

Due to their unique physical properties, waxes are high-value materials that are used in a variety of industrial applications. They are generated by chemical synthesis, extracted from fossil sources, or harvested from a small number of plant and animal species. As a result, the diversity of chemical structures in commercial waxes is low and so are their yields. These limitations can be overcome by engineering of wax biosynthetic pathways in the seeds of high-yielding oil crops to produce designer waxes for specific industrial end uses. In this review, we first summarize the current knowledge regarding the genes and enzymes generating the chemical diversity of cuticular waxes that accumulate at the surfaces of primary plant organs. We then consider the potential of cuticle biosynthetic genes for biotechnological wax production, focusing on selected examples of wax ester chain lengths and isomers. Finally, we discuss the genes/enzymes of cuticular alkane biosynthesis and their potential in future metabolic engineering of plants for the production of renewable hydrocarbon fuels.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.172
Teacher spread0.131 · 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