Glutamate receptors and synaptic plasticity: The impact of Evans and Watkins
Bibliographic record
Abstract
On the occasion of the 40 year anniversary of the hugely impactful review by Richard (Dick) Evans and Jeff Watkins, we describe how their work has impacted the field of synaptic plasticity. We describe their influence in each of the major glutamate receptor subtypes: AMPARs, NMDARs, KARs and mGluRs. Particular emphasis is placed on how their work impacted our own studies in the hippocampus. For example, we describe how the tools and regulators that they identified for studying NMDARs (e.g., NMDA, D-AP5 and Mg2+) led to the understanding of the molecular basis of the induction of LTP. We also describe how other tools that they introduced (e.g., (1S,3R)-ACPD and MCPG) helped lead to the concept of metaplasticity. This article is part of the Neuropharmacology Special Issue on ‘Glutamate Receptors – NMDA receptors’.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".