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Record W2063249182 · doi:10.1002/jnr.20562

Microglia in health and disease

2005· review· en· W2063249182 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Neuroscience Research · 2005
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsMicrogliaImmune systemMultiple sclerosisNeuroscienceInflammationNeuroinflammationNeurodegenerationProinflammatory cytokineNeurotrophic factorsDiseaseImmunologyBiologyCentral nervous systemMedicinePathologyReceptor

Abstract

fetched live from OpenAlex

Microglia, one of three glial cell types in the central nervous system (CNS), play an important role as resident immunocompetent and phagocytic cells in the CNS in the event of injury and disease. It was del Rio Hortega in 1927 who determined that microglia belong a distinct glial cell type apart from astrocytes and oligodendrocytes, and since 1970s there has been wide recognition that microglia are immune effectors in the CNS that respond to pathological conditions and participate in initiation and progression of neurological disorders including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and acquired immune deficiency syndrome dementia complex by releasing potentially cytotoxic molecules such as proinflammatory cytokines, reactive oxygen intermediates, proteinases and complement proteins. There is also evidence to suggest that microglia are capable of secreting neurotrophic or neuron survival factors upon activation via inflammation or injury. It is thus timely to review current status of knowledge on biology and immunology of microglia, and consider new directions of investigation on microglia in health and disease.

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.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.384
GPT teacher head0.511
Teacher spread0.127 · 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