MétaCan
Menu
← Back to cohort
Record W4396895755 · doi:10.1039/9781839165795-00290

Cannabinoid Neurotransmission: Neurotoxicity or Neuroprotection

2024· book-chapter· en· W4396895755 on OpenAlexaff
Ujendra Kumar

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeuroprotectionCannabinoidNeurotoxicityNeuroscienceNeurotransmissionPharmacologyMedicinePsychologyInternal medicineReceptorToxicity

Abstract

fetched live from OpenAlex

The changes in endocannabinoid system (ECS) neurotransmission are associated with neurotoxicity and neuroprotection in a healthy brain and during brain injury. Multifactorial interconnected events, including age, doses, route of administration, endogenous cannabinoids (eCBs), phytocannabinoids (phyto-CBs) or synthetic analogues, the enzymes involved in synthesis and degradation and cannabinoid (CB) receptor subtypes, play a determinant role in this dual effect. Moreover, the opposing effects are not only limited to in vitro conditions but have also been described in the experimental model of neurodegenerative diseases. Despite multiple mechanistic explanations for the neuroprotective or neurotoxic effect of CBs, the question “Are CBs toxic or beneficial to the brain” still awaits an answer. This chapter aims to demonstrate the multiple factors involved in cannabinoid neurotransmission and its impact on neurological and neuropsychological diseases.

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: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.007

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 head0.034
GPT teacher head0.301
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
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicCannabis and Cannabinoid Research→French-language works237,207→