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Record W2471088872 · doi:10.1007/978-0-387-75269-3_6

Excitatory Amino Acid Neurotransmitter Regulation

2009· book-chapter· en· W2471088872 on OpenAlexaff
Rochelle M. Hines, Alaa El‐Husseini

Bibliographic record

VenueMolecular Pain · 2009
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsExcitatory postsynaptic potentialNeurotransmitter receptorNeuroscienceSynapsePostsynaptic potentialPostsynaptic densityBiologyExcitatory synapseNeurotransmitterCompartmentalization (fire protection)NeurotransmissionSynaptic plasticityReceptorCell biologyInhibitory postsynaptic potentialCentral nervous systemBiochemistry

Abstract

fetched live from OpenAlex

Individual synapses vary enormously in their biochemical properties and functionality. The neurotransmitters released, the receptors activated, and the ensuing physiological responses are all variable, and susceptible to modification through a variety of mechanisms. The regulation of neurotransmitter receptors is a central mechanism by which the signaling properties of a synapse and a cell may be controlled. Excitatory neurotransmitter receptors are primarily localized to the postsynaptic dendritic compartment, anchored within the postsynaptic density (PSD). In their lifetime, receptors are subject to alternative splicing, differential sorting and compartmentalization. Moreover, these processes are influenced by activity driven protein trafficking, post-translational modifications and interaction with an overwhelmingly increasing number of proteins enriched at excitatory synapses. The diverse repertoire of regulatory mechanisms contributes to the amazing heterogeneity of synapse morphology and function in the central nervous system. Changes in receptor trafficking has been also implicated in shaping synaptic activity and plasticity, and defects in these processes may underlie several pathological states.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.289
Teacher spread0.252 · 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 designBench or experimental
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
Published2009
Admission routes1
Has abstractyes

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