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Record W7052966927

Synaptic clustering and strenghening by directed and activity-enhanced multiple-neurite convergence

2000· dissertation· en· W7052966927 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2000
Typedissertation
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsBibliothèque et Archives nationales du QuébecMcGill UniversityBibliographical Society of Canada
Fundersnot available
KeywordsNeuriteCluster analysisConvergence (economics)Synaptic plasticityAMPA receptorNerve netSynaptic scalingExponential growth
DOInot available

Abstract

fetched live from OpenAlex

Neuronal networks are specified by unique wiring patterns, however, it is not clear how these patterns are encoded into topographic maps of synaptic connections. We found networks in vitro and in vivo , where multiple-neurites converge and intersect at single sites non-randomly. At these sites, the density and activity of axonal terminals increased exponentially with the number of converging neurites. Multiple-neurite intersections were formed by a directed growth of neurites toward neurite intersections, they facilitated target switching by axons, and their frequency was elevated by activity through NMDA and AMPA glutamate receptors. Thus, clustering and strengthening of synaptic connections by activity-reinforced multiple-neurite convergence may serve to imprint information onto wiring patterns and synaptic maps.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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
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

Citations0
Published2000
Admission routes1
Has abstractyes

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