MétaCan
Menu
Back to cohort
Record W2946318369 · doi:10.1177/2398212819848213

Persistent memories of long-term potentiation and the <i>N</i> -methyl-d-aspartate receptor

2019· review· en· W2946318369 on OpenAlexaff
T.V.P. Bliss, G.L. Collingridge

Bibliographic record

VenueBrain and Neuroscience Advances · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsOccupational Cancer Research CentreLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsLong-term potentiationNeuroscienceLong-term depressionSynaptic plasticityTerm (time)Glutamate receptorReceptorPsychologyBiologyAMPA receptorPhysicsBiochemistry

Abstract

fetched live from OpenAlex

In this article, we describe our involvement in the early days of research into long-term potentiation. We start with a description of the early experiments conducted in Oslo and London where long-term potentiation was first characterised. We discuss the ways in which the molecular pharmacology of glutamate receptors control the induction and expression of long-term potentiation and its counterpart, long-term depression. We then go on to summarise the extraordinary advances in understanding the cellular mechanisms of synaptic plasticity that have taken place in the subsequent half century. Finally, the increasing evidence that impaired long-term potentiation is a core feature of many brain disorders (LToPathies) is addressed by way of a few selected examples.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.092
GPT teacher head0.393
Teacher spread0.301 · 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

Citations58
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueBrain and Neuroscience AdvancesSame topicNeuroscience and Neuropharmacology ResearchFrench-language works237,207