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Record W3139079540 · doi:10.1186/s42238-021-00062-4

The biosynthesis of the cannabinoids

2021· review· en· W3139079540 on OpenAlexafffund
M.N. Tahir, Simon Rondeau‐Gagné, John F. Trant

Bibliographic record

VenueJournal of Cannabis Research · 2021
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaMitacsArthritis SocietyUniversity of Windsor
KeywordsBiosynthesisChemistrySynthetic cannabinoidsBiochemistryCannabinoidGene

Abstract

fetched live from OpenAlex

Cannabis has been integral to Eurasian civilization for millennia, but a century of prohibition has limited investigation. With spreading legalization, science is pivoting to study the pharmacopeia of the cannabinoids, and a thorough understanding of their biosynthesis is required to engineer strains with specific cannabinoid profiles. This review surveys the biosynthesis and biochemistry of cannabinoids. The pathways and the enzymes' mechanisms of action are discussed as is the non-enzymatic decarboxylation of the cannabinoic acids. There are still many gaps in our knowledge about the biosynthesis of the cannabinoids, especially for the minor components, and this review highlights the tools and approaches that will be applied to generate an improved understanding and consequent access to these potentially biomedically-relevant materials.

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 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)0.011
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0010.004
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.005
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 head0.111
GPT teacher head0.461
Teacher spread0.350 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations184
Published2021
Admission routes2
Has abstractyes

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