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Record W4386316953 · doi:10.1002/9781119862611.ch9

The Endocannabinoid System

2023· other· en· W4386316953 on OpenAlexaff
Robin Saar, Sarah Dodd

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEndocannabinoid systemCannabinoid receptorCannabinoidAnxietyNeuroscienceAppetiteLipid signalingFight-or-flight responseReceptorPsychologyBiologyEndocrinologyMedicineInternal medicinePsychiatryGeneBiochemistry

Abstract

fetched live from OpenAlex

The endocannabinoid system is a regulatory system located in many parts of the body. Chemicals in this system work on both cannabinoid CB1 and CB2 receptors. When they bond there is a response that is designed to respond to the body and initiate changes. They increase when there is exercise, stress, and pain, at certain times of day, and are involved with appetite, coping, stress, and anxiety. When a stressful situation is repeated, cortisol levels will decrease over time, while in an endocannabinoid system, it continually increases in response to the situation. Normally, the system works in the right place at the right time; it is precise, responsive, and highly controlled. The endocannabinoidome is a complex signaling system with more than 100 lipid mediators and 50 protein metabolites of the endocannabinoid system. Perturbations in one system can cause alterations in other physiological systems bidirectionally, which can lead to health consequences in organs including the brain.

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)0.001
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: Other
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.009

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 head0.013
GPT teacher head0.290
Teacher spread0.277 · 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
Published2023
Admission routes1
Has abstractyes

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