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Record W2778605439 · doi:10.1002/dneu.22571

Microglial modulation of neuronal activity in the healthy brain

2017· review· en· W2778605439 on OpenAlexafffund
Elisa M. York, Louis‐Philippe Bernier, Brian A. MacVicar

Bibliographic record

VenueDevelopmental Neurobiology · 2017
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMicrogliaNeuroscienceBiologyCentral nervous systemNeuronal circuitsBrain functionPremovement neuronal activityHomeostasisBiological neural networkImmunologyInflammationCell biology

Abstract

fetched live from OpenAlex

Investigations on the role of microglia in the brain have traditionally been focused on their contributions to disease states. However, recent observations have now convincingly shown that microglia in the healthy brain are not passive bystanders, but instead play a critical role in both central nervous system development and homeostasis of synaptic circuits in the adult. Here, we review the various mechanisms by which microglia impact neuronal communication in the healthy adult brain, both by sensing nearby synaptic responses and by actively modulating neuronal function. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 593-603, 2018.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
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 head0.208
GPT teacher head0.386
Teacher spread0.178 · 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

Citations103
Published2017
Admission routes2
Has abstractyes

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