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Record W4406321802 · doi:10.1007/978-1-59259-105-3

Neuroglia in the Aging Brain

2002· book· en· W4406321802 on OpenAlexfundno aff

Bibliographic record

VenueHumana Press eBooks · 2002
Typebook
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
FundersDepartment of Pathology, Johns Hopkins UniversityAdvanced Scientific Computing ResearchUniversity of North Carolina at Chapel HillOffice of International Science and EngineeringGastroenterological Society of AustraliaUniversity of AlabamaEberhard Karls Universität TübingenWake Forest UniversityJohns Hopkins UniversityInstitut National de la Santé et de la Recherche MédicaleUniversidad de GranadaUniversity of Texas Medical BranchUniversity of AlbertaUniversity of WashingtonUniversity of Alabama at BirminghamUniversidad de CantabriaUniversity of Miami
KeywordsAging brainBrain agingNeurosciencePsychologyCognition

Abstract

fetched live from OpenAlex

A distinguished panel of internationally recognized neuroscientists comprehensively review the involvement of and changes in glial cells both during the normal aging process and in the major disorders of old age. Topics range from the cellular and molecular changes that occur with aging-especially aging-associated activation of astrocytes and microglia and its relation to neuronal injury and repair-to neuron-glia intercommunication. The contributors show how glial signals may be modulated by hormones, growth factors, neurotransmitters, intracellular metabolism, and intercellular exchanges, as well as by aging of the blood-brain barrier.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.007

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 head0.299
Teacher spread0.207 · 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
GenreOther

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

Citations4
Published2002
Admission routes1
Has abstractyes

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