MétaCan
Menu
Back to cohort
Record W1982494334 · doi:10.1212/wnl.0b013e3181c97d04

The interplay between the immune and central nervous systems in neuronal injury

2009· article· en· W1982494334 on OpenAlexaff
V. Wee Yong, Steven C. Marks

Bibliographic record

VenueNeurology · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsImmune systemMicrogliaProinflammatory cytokineNeuroprotectionCentral nervous systemMultiple sclerosisBiologyNeuroscienceImmunologyNeuroinflammationInflammation

Abstract

fetched live from OpenAlex

Once perceived as a region of limited immune activity, the CNS is now known to be an important site of immune interactions. Activated T cells can infiltrate the blood-brain barrier where they accumulate and proliferate in response to antigen restimulation. These leukocytes express proinflammatory cytokines that help in activating microglia and other immune cells. A profound inflammatory response ensues, which can lead to axonal injury and demyelination. In contrast, other T cells can be neuroprotective. CD4(+) Th2 cells secrete anti-inflammatory cytokines and can elicit the production of bioactive neurotrophins from CNS glia. In addition, neurons themselves can contribute to immune system regulation by being targets of neurotoxic T cells or by altering T-cell activity, including the generation of regulatory T cells. The interplay between components of the immune system and CNS contributes both to healthy brain function and to the pathogenesis of neurodegenerative diseases such as multiple sclerosis.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations45
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueNeurologySame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207