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Record W2997137838 · doi:10.1212/nxg.0000000000000389

HSAN-VI

2020· article· en· W2997137838 on OpenAlexaff
Anisha Lynch‐Godrei, Rashmi Kothary

Bibliographic record

VenueNeurology Genetics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGene isoformNull alleleDystoniaAllelePathogenesisMutationGeneDiseaseCompound heterozygosityGeneticsBiologyMedicineImmunologyPathologyNeuroscience

Abstract

fetched live from OpenAlex

Hereditary sensory and autonomic neuropathy (HSAN-VI) is a recessive genetic disorder that arises because of mutations in the human dystonin gene (DST, previously known as bullous pemphigoid antigen 1). Although initial characterization of HSAN-VI reported it as a sensory neuropathy that was lethal in infancy, we now know of a number of heterozygous mutations in DST that result in milder forms of the disease. Akin to what we observe in the mouse model dystonia musculorum (Dstdt), we believe that the heterogeneity of HSAN-VI can be attributed to a number of dystonin isoforms that the mutation affects. Lack of neuronal isoform dystonin-a2 is likely the universal determinant of HSAN-VI because all reported human cases are null for this isoform, as are all Dstdt mouse alleles. Compensatory mechanisms by intact dystonin-a isoforms also likely play a role in regulating disease severity, although we have yet to determine what specific effect dystonin-a1 and dystonin-a3 have on the pathogenesis of HSAN-VI.

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 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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.022
GPT teacher head0.268
Teacher spread0.246 · 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 designNot applicable
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

Citations16
Published2020
Admission routes1
Has abstractyes

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