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Adenosine — A peripheral neuronal modulator of pain and inflammation

2003· book-chapter· en· W107561166 on OpenAlexaff
Jana Sawynok

Bibliographic record

VenueBirkhäuser Basel eBooks · 2003
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAdenylyl cyclaseAdenosinePhospholipase CAdenosine receptorReceptorG protein-coupled receptorADCY6G proteinPurinergic signallingChemistryCell biologyAdenosine A3 receptorGs alpha subunitInternal medicineEndocrinologyBiologyBiochemistryMedicineAgonist

Abstract

fetched live from OpenAlex

In the central nervous system, adenosine plays an important physiological role in the regulation of neuronal activity and in neuroprotection. Adenosine actions are mediated by cell surface adenosine receptors (A1, A2A, A2B, A3) which are all linked to G-proteins, and activation of these receptors can recruit a number of second messenger systems [1,2] (Tab. 1). Adenosine has a high affinity (sub-micromolar) for A1 receptors (which are widely distributed) and A2A receptors (which have a more restricted distribution), and a lower affinity (micromolar) for A2B and A3 receptors (which are present at much lower levels throughout) [1,2].

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 score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.206
Teacher spread0.195 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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