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Record W2567485069 · doi:10.1002/ana.24855

<scp><i>KCNA2</i></scp> mutations are rare in hereditary spastic paraplegia

2016· letter· en· W2567485069 on OpenAlexafffund
Ziv Gan‐Or, Grace Yoon, Oksana Suchowersky, Nicolas Dupré, Guy A. Rouleau

Bibliographic record

VenueAnnals of Neurology · 2016
Typeletter
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsUniversité LavalUniversity of AlbertaMontreal Neurological Institute and HospitalSickKids FoundationUniversity of TorontoMcGill UniversityHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsMedicineNeurologyHereditary spastic paraplegiaFamily medicineLibrary sciencePsychiatryGenetics

Abstract

fetched live from OpenAlex

This is the peer reviewed version of the following article: [Gan-Or, Z., Yoon, G., Suchowersky, O., Dupré, N., and Rouleau, G.A. (2017). KCNA2\n mutations are rare in hereditary spastic paraplegia. Annals of Neurology 81, 325–326.], which has been published in final form at https://doi.org/10.1002/ana.24855. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@openaccessbutton.org.

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 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)0.000
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.091
GPT teacher head0.302
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2016
Admission routes2
Has abstractyes

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