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Record W4391111413 · doi:10.1089/can.2023.0168

Cannabis Roots: Therapeutic, Biotechnological and Environmental Aspects

2024· article· en· W4391111413 on OpenAlexaffabout
Valérie Gagné, Nathalie Boucher, Isabel Desgagné‐Penix

Bibliographic record

VenueCannabis and Cannabinoid Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité du Québec à Trois-RivièresInnovation and Economic Development Trois Rivières
Fundersnot available
KeywordsLegalizationCannabisBiotechnologyRecreationPhytoremediationEffects of cannabisBiologyMedicineEcologyPsychiatry

Abstract

fetched live from OpenAlex

Since the legalization of recreational cannabis in Canada in 2018, the number of licenses for this crop has increased significantly, resulting in an increase in waste generated. Nevertheless, cannabis roots were once used for their therapeutic properties, indicating that they could be valued today rather than dismissed. This review will focus on both traditional therapeutic aspects and potential use of roots in modern medicine while detailing the main studies on active phytomolecules found in cannabis roots. The environmental impact of cannabis cultivation and current knowledge of the root-associated microbiome are also presented as well as their potential applications in biotechnology and phytoremediation. Thus, several high added-value applications of cannabis roots resulting from scientific advances in recent years can be considered to remove them from discarded residues.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.329
Teacher spread0.300 · 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
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

Citations4
Published2024
Admission routes2
Has abstractyes

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