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Record W2101766473 · doi:10.1186/1756-6606-2-36

Action potential evoked transmitter release in central synapses: insights from the developing calyx of Held

2009· review· en· W2101766473 on OpenAlexafffund
Lu‐Yang Wang, Michael J. Fedchyshyn, Yi Yang

Bibliographic record

VenueMolecular Brain · 2009
Typereview
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNeurosciencePostsynaptic potentialNeurotransmissionSynapseContext (archaeology)BiologySynaptic plasticityReceptor

Abstract

fetched live from OpenAlex

Chemical synapses are the fundamental units that mediate communication between neurons in the mammalian brain. In contrast to the enormous progress made in mapping out postsynaptic contributions of receptors, scaffolding structures and receptor trafficking to synaptic transmission and plasticity, the small size of nerve terminals has largely precluded direct analyses of presynaptic modulation of excitability and transmitter release in central synapses. Recent studies performed in accessible synapses such as the calyx of Held, a giant axosomatic synapse in the sound localization circuit of the auditory brainstem, have provided tremendous insights into how central synapses regulate the dynamic gain range of synaptic transmission. This review will highlight experimental evidence that resolves several long-standing issues with respect to intricate interplays between the waveform of action potentials, Ca2+ currents and transmitter release and further conceptualize their relationships in a physiological context with theoretical models of the spatial organization of voltage-gated Ca2+ channels and synaptic vesicles at release sites.

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: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.033
GPT teacher head0.284
Teacher spread0.251 · 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
GenreReview

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

Citations56
Published2009
Admission routes2
Has abstractyes

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