MétaCan
Menu
Back to cohort
Record W2112538318 · doi:10.1038/nn.3230

Divergent roles of ALS-linked proteins FUS/TLS and TDP-43 intersect in processing long pre-mRNAs

2012· article· en· W2112538318 on OpenAlexaff
Clotilde Lagier‐Tourenne, Magdalini Polymenidou, Kasey R. Hutt, Anthony Q. Vu, Michael W. Baughn, Stephanie C. Huelga, Kevin M. Clutario, Shuo‐Chien Ling, Tiffany Y Liang, Curt Mazur, Edward V. Wancewicz, Aneeza S. Kim, Andy Watt, Sue Freier, Geoffrey G. Hicks, John P. Donohue, Lily Shiue, C. Frank Bennett, John Ravits, Don W. Cleveland, G Yeo

Bibliographic record

VenueNature Neuroscience · 2012
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Neurological Disorders and StrokeNational Human Genome Research InstituteNational Institute of General Medical SciencesWellcome Trust
KeywordsBiologyRNA splicingIntronRNA-binding proteinAmyotrophic lateral sclerosisCell biologyGeneRNA recognition motifAlternative splicingMessenger RNARNAMolecular biologyGeneticsPathologyMedicine

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.026
GPT teacher head0.334
Teacher spread0.308 · 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

Citations750
Published2012
Admission routes1
Has abstractno

Explore more

Same venueNature NeuroscienceSame topicAmyotrophic Lateral Sclerosis ResearchFrench-language works237,207