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Record W2095283539 · doi:10.4161/rna.32091

Unmasking the messenger

2014· review· en· W2095283539 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRNA Biology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsBiologySynapseTranslation (biology)NeuroscienceSynaptic plasticityMessenger RNAGene expressionRegulation of gene expressionCell biologyGeneGenetics

Abstract

fetched live from OpenAlex

Synaptic plasticity, learning, and memory require high temporal and spatial control of gene expression. These processes are thought to rely mainly on asymmetric mRNA transport to synapses. Already in the early days of studying mRNA transport, Wilhelm and Vale proposed a multi-step process in 1993. Since then, we have gained important novel insights into how these individual steps are controlled by research performed in various cell types and organisms. Here, we present the latest view on how dendritic mRNA localization is achieved and how local translation at the synapse is regulated. In particular, we propose that the recently observed heterogeneity of RNA-protein particle assembly in neurons might be the key for how precise gene expression in the brain is achieved. In addition, we focus on latest data dealing with translational activation of translationally repressed mRNPs at a synapse that experiences learning-induced changes in its morphology and function. Together, these new findings shed new light on how precise regulatory mechanisms can lead to synaptic plasticity and memory formation.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.035
GPT teacher head0.371
Teacher spread0.336 · 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