MétaCan
Menu
Back to cohort
Record W2123228137 · doi:10.1186/2045-5380-3-19

Translational evidence for the involvement of the endocannabinoid system in stress-related psychiatric illnesses

2013· article· en· W2123228137 on OpenAlexafffund
Matthew N. Hill, Sachin Patel

Bibliographic record

VenueBiology of Mood & Anxiety Disorders · 2013
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Calgary
FundersNational Institute of Mental HealthCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsAmygdalaAnxietyEndocannabinoid systemMoodNeurosciencePrefrontal cortexPsychologyDepression (economics)Mood disordersPsychiatryClinical psychologyMedicineCognitionReceptorInternal medicine

Abstract

fetched live from OpenAlex

Accumulating evidence over the past decade has highlighted an important role of the endocannabinoid (eCB) system in the regulation of stress and emotional behavior across divergent species, from rodents to humans. The general findings from this work indicate that the eCB system plays an important role in gating and buffering the stress response, dampening anxiety and regulating mood. Work in rodents has allowed researchers to determine the neural mechanisms mediating this relationship while work in human populations has demonstrated the possible importance of this system in stress-related psychiatric diseases, such as post-traumatic stress disorder, generalized anxiety and major depression. These stress-protective effects of eCB signaling appear to be primarily mediated by their actions within corticolimbic structures, particularly the amygdala and the prefrontal cortex. The aim of this review is to provide an up-to-date discussion of the current level of knowledge in this field, as well as address the current gaps in knowledge and specific areas of research that require attention.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.019
GPT teacher head0.292
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations111
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueBiology of Mood & Anxiety DisordersSame topicCannabis and Cannabinoid ResearchFrench-language works237,207