MétaCan
Menu
Back to cohort
Record W2021828702 · doi:10.1016/j.ajhg.2009.09.019

Spinocerebellar Ataxia Type 31 Is Associated with “Inserted” Penta-Nucleotide Repeats Containing (TGGAA)n

2009· article· en· W2021828702 on OpenAlexfundno aff
Nozomu Sato, Takeshi Amino, Kazuhiro Kobayashi, Shuichi Asakawa, Taro Ishiguro, Taiji Tsunemi, Makoto Takahashi, Tohru Matsuura, Kevin M. Flanigan, Sawa Iwasaki, Fumitoshi Ishino, Yuko Saito, Shigeo Murayama, Mari Yoshida, Yoshio Hashizume, Yuji Takahashi, Shoji Tsuji, Nobuyoshi Shimizu, Tatsushi Toda, Kinya Ishikawa, Hidehiro Mizusawa

Bibliographic record

VenueThe American Journal of Human Genetics · 2009
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersHospital for Sick ChildrenMinistry of Health, Labour and WelfareMinistry of Education, Culture, Sports, Science and Technology
KeywordsBiologyIntronGeneticsSpinocerebellar ataxiaRNA splicingMolecular biologyDirect repeatAtaxiaTrinucleotide repeat expansionGeneRNAAlleleGenome

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.037
GPT teacher head0.292
Teacher spread0.255 · 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

Citations302
Published2009
Admission routes1
Has abstractno

Explore more

Same venueThe American Journal of Human GeneticsSame topicGenetic Neurodegenerative DiseasesFrench-language works237,207