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Record W4407422461 · doi:10.4103/aian.aian_166_24

Oculodentodigital Dysplasia Presenting as Spastic Ataxic Syndrome in an Indian Patient

2025· article· en· W4407422461 on OpenAlexaboutno aff
Gosala RK Sarma, Abhinaya Varidireddy, GG Sharath, Sunitha Palasamudram Kumaran

Bibliographic record

VenueAnnals of Indian Academy of Neurology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtaxic GaitSpasticDermatologyAtaxiaPhysical medicine and rehabilitationPsychiatryCerebral palsy

Abstract

fetched live from OpenAlex

Spastic ataxic syndrome is a combination of cerebellar ataxia with spasticity and other pyramidal features. Common causes of spastic ataxic syndrome include spinocerebellar ataxia (SCA) 1, SCA2, autosomal recessive ataxia of Charlevoix-Saguenay, Friedreich ataxia, and hereditary spastic paraplegia type-7. We report a 32-year-old female who presented with unsteadiness of gait, incoordination, and tremulousness of both hands for 10 years with microphthalmia, microdontia, dental caries, and syndactyly. Magnetic resonance imaging of the brain showed T2 fluid-attenuated inversion recovery hyper intensities in periventricular and lobar white matter and internal capsule. Thus, we report a genetically confirmed oculodentodigital dysplasia (ODDD), an autosomal dominant disorder, in an Indian patient who presented with spastic ataxic syndrome, a rarity that has not been reported so far.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.309
Teacher spread0.287 · 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 designCase report
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

Citations0
Published2025
Admission routes1
Has abstractyes

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