MétaCan
Menu
Back to cohort
Record W2105959579 · doi:10.1007/s11302-006-9046-7

Adenosine in inflammatory joint diseases

2007· article· en· W2105959579 on OpenAlexfundno aff
Edwin S. L. Chan, Paula Fernández, Bruce N. Cronstein

Bibliographic record

VenuePurinergic Signalling · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Center for Research ResourcesNational Institute of General Medical SciencesNational Institute on Alcohol Abuse and AlcoholismNational Institutes of HealthSchool of Medicine, New York UniversityYork UniversityNational Institute of Diabetes and Digestive and Kidney DiseasesScleroderma Foundation
KeywordsAdenosineMedicinePurinergic receptorInflammationPurinergic signallingImmune systemDiseaseImmunologyBioinformaticsAdenosine receptorBiologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Inflammatory joint diseases are a group of heterogeneous disorders with a variety of different etiologies and disease manifestations. However, there are features that are common to all of them: first, the recruitment of various inflammatory cell types that are attracted to involved tissues over the course of the disease process. Second, the treatments used in many of these diseases are commonly medications that suppress or alter immune function. The demonstration that adenosine has endogenous anti-inflammatory functions and that some of the most commonly used anti-rheumatic medications exert their therapeutic effects through stimulation of adenosine release suggest an important role for purinergic signaling in inflammatory rheumatic disorders.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.235
Teacher spread0.225 · 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 designObservational
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

Citations19
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePurinergic SignallingSame topicAdenosine and Purinergic SignalingFrench-language works237,207