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Record W3106216927 · doi:10.1139/gen-2020-0087

The genetics of <i>Cannabis</i>—genomic variations of key synthases and their effect on cannabinoid content

2020· review· en· W3106216927 on OpenAlexaffvenueabout
Aparna Singh, Andriy Bilichak, Igor Kovalchuk

Bibliographic record

VenueGenome · 2020
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Lethbridge
Fundersnot available
KeywordsBiologyCannabinoidCannabisGenomeGeneticsGeneCannabis sativaBiotechnologyBotany

Abstract

fetched live from OpenAlex

Despite being a controversial crop, Cannabis sativa L. has a long history of cultivation throughout the world. Following recent legalization in Canada, Cannabis is emerging as an important plant for both medicinal and recreational purposes. Recent progress in genome sequencing of both cannabis and hemp varieties allow for systematic analysis of genes coding for enzymes involved in the cannabinoid biosynthesis pathway. Single-nucleotide polymorphisms in the coding regions of cannabinoid synthases play an important role in determining plant chemotype. Deep understanding of how these variants affect enzyme activity and accumulation of cannabinoids will allow breeding of novel cultivars with desirable cannabinoid profiles. Here we present a short overview of the major cannabinoid synthases and present the data on the analysis of their genetic variants and their effect on cannabinoid content using several in-house sequenced Cannabis cultivars.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.306
Teacher spread0.267 · 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 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

Citations27
Published2020
Admission routes3
Has abstractyes

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