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Record W2048862315 · doi:10.1038/nature11628

Autism-related deficits via dysregulated eIF4E-dependent translational control

2012· article· en· W2048862315 on OpenAlexafffund
Christos G. Gkogkas, Arkady Khoutorsky, Israeli Ran, Emmanouil Rampakakis, Tatiana Nevarko, D. Weatherill, Cristina Vasuta, Stephanie S. Yee, Morgan Truitt, Paul Dallaire, François Major, Paul Lasko, Davide Ruggero, Karim Nader, Jean‐Claude Lacaille, Nahum Sonenberg

Bibliographic record

VenueNature · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and CancerMcGill University
FundersNational Institute of General Medical SciencesNational Cancer InstituteCanadian Institutes of Health Research
KeywordsNeuroliginEIF4ETranslation (biology)AutismPI3K/AKT/mTOR pathwayExcitatory postsynaptic potentialInhibitory postsynaptic potentialNeuroscienceRepressorBiologySynaptic plasticityPostsynaptic potentialCell biologyMessenger RNAGeneSignal transductionPsychologyGeneticsReceptorGene expressionPsychiatry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.207
Teacher spread0.204 · 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 designBench or experimental
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

Citations531
Published2012
Admission routes2
Has abstractno

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