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The Genomics of Cannabis and Its Close Relatives

2020· review· en· W3011908650 on OpenAlexaff
Igor Kovalchuk, Marco Pellino, Philippe Rigault, Robin van Velzen, Jana Ebersbach, Joanne R. Ashnest, Martin Mau, M. Eric Schranz, Jane Alcorn, Robert B. Laprairie, John McKay, Connor Burbridge, David J. Schneider, Daniela Vergara, Nolan C. Kane, Timothy F. Sharbel

Bibliographic record

VenueAnnual Review of Plant Biology · 2020
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicHops Chemistry and Applications
Canadian institutionsDalhousie UniversityAgriculture and Agri-Food CanadaUniversité du QuébecUniversity of SaskatchewanUniversity of Lethbridge
Fundersnot available
KeywordsCannabisGenomicsBiologyGenomeEvolutionary biologyGeneticsPsychologyGenePsychiatry

Abstract

fetched live from OpenAlex

Cannabis sativa L. is an important yet controversial plant with a long history of recreational, medicinal, industrial, and agricultural use, and together with its sister genus Humulus , it represents a group of plants with a myriad of academic, agricultural, pharmaceutical, industrial, and social interests. We have performed a meta-analysis of pooled published genomics data, andwe present a comprehensive literature review on the evolutionary history of Cannabis and Humulus , including medicinal and industrial applications. We demonstrate that current Cannabis genome assemblies are incomplete, with ∼10% missing, 10–25% unmapped, and 45S and 5S ribosomal DNA clusters as well as centromeres/satellite sequences not represented. These assemblies are also ordered at a low resolution, and their consensus quality clouds the accurate annotation of complete, partial, and pseudogenized gene copies. Considering the importance of genomics in the development of any crop, this analysis underlines the need for a coordinated effort to quantify the genetic and biochemical diversity of this species.

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 score0.005
Threshold uncertainty score0.010

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.115
GPT teacher head0.475
Teacher spread0.360 · 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

Citations150
Published2020
Admission routes1
Has abstractyes

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