MétaCan
Menu
Back to cohort
Record W2488539909 · doi:10.1385/0-89603-078-4:139

Muscarinic Cholinergic Receptors

2003· book-chapter· en· W2488539909 on OpenAlexaff
Andrew P. Braun, Prakash V. Sulakhe

Bibliographic record

VenueHumana Press eBooks · 2003
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMuscarinic acetylcholine receptorCholinergicNicotinic agonistNeuroscienceAcetylcholineAcetylcholine receptorNeurotransmitter receptorMuscarinic acetylcholine receptor M4Muscarinic acetylcholine receptor M5BiologyReceptorNeurotransmitterPopulationMuscarinic acetylcholine receptor M2Cholinergic neuronCentral nervous systemEndocrinologyMuscarinic acetylcholine receptor M3Internal medicineMedicineBiochemistry

Abstract

fetched live from OpenAlex

In the central nervous system (CNS), modulation of neuronal activity is brought about by the actions of endogenous “neurotransmitters” that specifically interact with receptor proteins located in the neuronal cell membrane. In the cholinergic system, acetylcholine is the primary neurotransmitter released in the CNS, and appears to alter neuronal excitability by affecting such processes as cGMP production and K + flux ( Heilbronn and Bartfai, 1978 ). In contrast to the periphery, in which the cholinergic receptor population is divided between nicotinic and muscarinic subclasses, the CNS-associated cholinergic receptor appears to be predominantly of the muscarinic type, although there is evidence that the spinal cord contains substantial amounts of nicotinic receptors ( Heilbronn and Bartfai, 1978 ). Historically, the initial characterization of cholinergic actions was provided by A. S. V. Burgen. Although these early studies, using smooth muscle tissue ( Burgen and Spero, 1968 ; Burgen et al., 1974 ), provided initial clues about the peripheral muscarinic receptors, since then there have been numerous investigations, especially following the advent of radioligand binding assays, from which have come many novel observations of physiological significance. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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: Other · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.039

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 head0.039
GPT teacher head0.247
Teacher spread0.208 · 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

Citations21
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueHumana Press eBooksSame topicReceptor Mechanisms and SignalingFrench-language works237,207