MétaCan
Menu
Back to cohort
Record W2601071569 · doi:10.1371/journal.pone.0173911

Terpene synthases from Cannabis sativa

2017· article· en· W2601071569 on OpenAlexafffund
Judith K. Booth, Jonathan E. Page, Jörg Bohlmann

Bibliographic record

VenuePLoS ONE · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsTerpeneTrichomeLimoneneTerpenoidHumuleneBiologyBotanyCannabis sativaCannabisMyrceneInflorescenceBiochemistryEssential oilMedicine

Abstract

fetched live from OpenAlex

Cannabis (Cannabis sativa) plants produce and accumulate a terpene-rich resin in glandular trichomes, which are abundant on the surface of the female inflorescence. Bouquets of different monoterpenes and sesquiterpenes are important components of cannabis resin as they define some of the unique organoleptic properties and may also influence medicinal qualities of different cannabis strains and varieties. Transcriptome analysis of trichomes of the cannabis hemp variety 'Finola' revealed sequences of all stages of terpene biosynthesis. Nine cannabis terpene synthases (CsTPS) were identified in subfamilies TPS-a and TPS-b. Functional characterization identified mono- and sesqui-TPS, whose products collectively comprise most of the terpenes of 'Finola' resin, including major compounds such as β-myrcene, (E)-β-ocimene, (-)-limonene, (+)-α-pinene, β-caryophyllene, and α-humulene. Transcripts associated with terpene biosynthesis are highly expressed in trichomes compared to non-resin producing tissues. Knowledge of the CsTPS gene family may offer opportunities for selection and improvement of terpene profiles of interest in different cannabis strains and varieties.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.032
GPT teacher head0.227
Teacher spread0.195 · 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 designBench or experimental
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

Citations260
Published2017
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicPlant biochemistry and biosynthesisFrench-language works237,207