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Record W3142192179 · doi:10.1007/s12079-021-00614-6

A network map of apelin-mediated signaling

2021· article· en· W3142192179 on OpenAlexaff
Shobha Dagamajalu, Rex Devasahayam Arokia Balaya, Pushparani Devi Philem, Jan K. Rainey, Thottethodi Subrahmanya Keshava Prasad

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2021
Typearticle
Languageen
FieldMedicine
TopicApelin-related biomedical research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsApelinBiologySignal transductionG protein-coupled receptorPI3K/AKT/mTOR pathwayCell biologyProtein kinase BReceptorGenetics

Abstract

fetched live from OpenAlex

The apelin receptor (APLNR) is a class A (rhodopsin-like) G-protein coupled receptor with a wide distribution throughout the human body. Activation of the apelin/APLNR system regulates AMPK/PI3K/AKT/mTOR and RAF/ERK1/2 mediated signaling pathways. APLNR activation orchestrates several downstream signaling cascades, which play diverse roles in physiological effects, including effects upon vasoconstriction, heart muscle contractility, energy metabolism regulation, and fluid homeostasis angiogenesis. We consolidated a network map of the APLNR signaling map owing to its biomedical importance. The curation of literature data pertaining to the APLNR system was performed manually by the NetPath criteria. The described apelin receptor signaling map comprises 35 activation/inhibition events, 38 catalysis events, 4 molecular associations, 62 gene regulation events, 113 protein expression types, and 4 protein translocation events. The APLNR signaling pathway map data is made freely accessible through the WikiPathways Database ( https://www.wikipathways.org/index.php/Pathway:WP5067 ).

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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

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 head0.030
GPT teacher head0.304
Teacher spread0.274 · 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

Citations20
Published2021
Admission routes1
Has abstractyes

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