MétaCan
Menu
Back to cohort
Record W3003176227 · doi:10.3390/microorganisms8030355

Cannabis Microbiome and the Role of Endophytes in Modulating the Production of Secondary Metabolites: An Overview

2020· review· en· W3003176227 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicroorganisms · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsMicrobiomeCannabisBiologyBiotechnologyComputational biologyMedicineBioinformaticsPsychiatry

Abstract

fetched live from OpenAlex

host distinct beneficial microbial communities on and inside their tissues and organs, including seeds. They contribute to plant growth, facilitating mineral nutrient uptake, inducing defence resistance against pathogens, and modulating the production of plant secondary metabolites. Understanding the microbial partnerships with cannabis has the potential to affect the agricultural practices by improving plant fitness and the yield of cannabinoids. Little is known about this beneficial cannabis-microbe partnership, and the complex relationship between the endogenous microbes associated with various tissues of the plant, and the role that cannabis may play in supporting or enhancing them. This review will consider cannabis microbiota studies and the effects of endophytes on the elicitation of secondary metabolite production in cannabis plants. The review aims to shed light on the importance of the cannabis microbiome and how cannabinoid compound concentrations can be stimulated through symbiotic and/or mutualistic relationships with endophytes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.242
Teacher spread0.222 · 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