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Hereditary spastic paraplegia in Japan

2011· article· en· W2327643467 on OpenAlexaboutno aff
Yoshihisa Takiyama

Bibliographic record

VenueRinsho Shinkeigaku · 2011
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHereditary spastic paraplegiaParaplegiaSpasticMedicinePhysical medicine and rehabilitationPhysical therapyBiologyGeneticsSpinal cordGeneCerebral palsyPhenotypePsychiatry

Abstract

fetched live from OpenAlex

The Japan Spastic Paraplegia Research Consortium (JASPAC) is conducting a nationwide clinical and genetic survey of patients with HSP in Japan. To date (July 20, 2011), 375 index patients with HSP from 42 prefectures in Japan have been registered. In 148 Japanese ADHSP families, SPG4 was the most common form, accounting for 47%, followed by SPG31 (4%), SPG3A (3%), SPG8 (1%), and SPG10 (1%). Meanwhile, preliminary data showed that SPG11 and ARSACS were common in Japanese ARHSP families. Since the genes in approximately 40% of ADHSP and 80% of ARHSP cases remain unknown, we aim to identify the new genes responsible for HSP. We are now searching for a novel gene responsible for ARHSP with optic atrophy and neuropathy. To date, non-Quebec patients with ARSACS have been found in the Mediterranean area, Europe and Japan. Although Quebec patients show a homogeneous phenotype, Japanese patients exhibit some atypical clinical features, as follows: slightly later onset than that in Quebec patients, absence of retinal hypermyelination, intellectual impairment, and lack of spasticity. Recently, we found characteristic MRI findings in eight Japanese ARSACS patients, who all exhibited linear hypointensity in the pons and a hypointense area in the middle cerebellar peduncles in T(2) weighted and FLAIR images.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.096
GPT teacher head0.255
Teacher spread0.158 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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