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Record W3016708381 · doi:10.32396/usurj.v6i2.460

The Changing Brain

2020· article· en· W3016708381 on OpenAlexaffvenue
Michael Kevin Bergen

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNeurogenesisNeuroscienceNeuroplasticitySynaptic plasticityLong-term potentiationNeurotrophic factorsPsychologyRegulatorMetaplasticityExcitatory postsynaptic potentialBiologyBrain-derived neurotrophic factorEndocannabinoid systemNeurotrophinInhibitory postsynaptic potentialReceptor

Abstract

fetched live from OpenAlex

The brain remains the most complex organ within the mammalian body with an immense capacity for plasticity and change throughout an individual’s life history. This review examines brain-derived neurotrophic factor (BDNF) and endocannabinoid (eCB) signalling cross-talk within a variety of neurodevelopmental, genic, and plastic processes that occur in the brain. The action of eCB and BDNF cross-talk in embryonic and adult neurogenesis is a bidirectional dynamic process of high complexity that facilitates neural proliferation, differentiation, spatial development, synaptic development, and programmed cell death events. The coupled action of BDNF eCB signalling serves as a functional regulator of neuroplasticity, modulating synaptic signalling strength within both inhibitory and excitatory neurons. This also regulates long-term potentiation and long-term depression processes, which play important roles in the neurobiology of learning and memory. Understanding BDNF and eCB signalling has the potential to offer new insights into brain function and develop novel therapeutic treatment for psychiatric disorders, neurodegenerative disorders, and brain injury recovery.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0280.009

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 head0.038
GPT teacher head0.302
Teacher spread0.264 · 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
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

Citations1
Published2020
Admission routes2
Has abstractyes

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Same venueUSURJ University of Saskatchewan Undergraduate Research JournalSame topicCannabis and Cannabinoid ResearchFrench-language works237,207