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Record W2078368985 · doi:10.4236/ojgen.2013.32a3007

Diagnostic challenges in Salla disease

2013· article· en· W2078368985 on OpenAlexaff
Jessica N. Hartley, Michael S. Salman, Frances Booth, Lorne E. Seargeant, David A. Wenger, Jens Wrogemann, Aizeddin Mhanni

Bibliographic record

VenueOpen Journal of Genetics · 2013
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsShared HealthUniversity of Manitoba
Fundersnot available
KeywordsSialic acidDiseaseMedicineMagnetic resonance imagingPathologyBiologyGeneticsRadiology

Abstract

fetched live from OpenAlex

Sialic acid storage disease (Salla disease) is an autosomal recessive disorder caused by mutations in a lysosomal sialic acid export protein, SLC17A5 (OMIM #604369). This disorder was initially described in Northern Finland but more recently has been reported in patients of other ethnicities. We describe the clinical presentation and the neuroimaging findings of two non-Finnish children where a diagnosis of Salla disease was suspected on the basis of brain magnetic resonance imaging. The biochemical confirmation of this diagnosis posed a challenge as both patients had elevated percent free urine sialic acid but biochemical analyses in fibroblasts were not conclusive; therefore, molecular testing was necessary for confirmation of the diagnosis. The described encounters demonstrate the importance of pursuing confirmatory molecular diagnostic testing when a sialic acid storage disorder is suspected.

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)0.007
metaresearch head score (Gemma)0.020
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 score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.003
Scholarly communication0.0020.003
Open science0.0030.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.085
GPT teacher head0.355
Teacher spread0.269 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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