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Record W201521138

[Tay-Sachs disease in non-Jewish infant in Israel].

2012· article· en· W201521138 on OpenAlexaboutno aff
Nasser Nadim

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsTay-Sachs diseaseMedicinePediatricsDiseaseHyperreflexiaNystagmusSurgeryPsychiatryPathology
DOInot available

Abstract

fetched live from OpenAlex

Tay-Sachs disease, also known as GM2 gangliosidosis or Hexosaminidase A deficiency is an autosomal recessive genetic fatal disorder. The disease is known to appear in East European Ashkenazi Jews, North African Jews, and Quebec French Canadians exclusively, but, with different frequency and type of mutation. Its most common variant is the infantile type Tay-Sachs disease. Juvenile and late-onset forms of the disease are infrequent and slowly progressive. At nearly 3 to 6 months old, a baby with Tay-Sachs progressively loses his motor skills and attentiveness. Startle responses and hyperreflexia become prominent, especially on eliciting deep patellar and Achilles reflexes, as a consequence of neurodegeneration of the upper motor neuron. Other systemic damage ensues gradually; seizures, blindness, spasticity of limbs, inability to swallow and breathe, and eventually the baby dies at 1-4 years of age. All Tay-Sachs patients have a "cherry red spot", easily seen in the macula area of the retina, using an ophthalmoscope. The "cherry red spot" is the only normal part of the retina in these sick babies. The case presented here emphasizes that Tay-Sachs disease is sometimes misdiagnosed at first visits even by an experienced clinician, because of his lack of awareness that this disease is not exclusively a Jewish disease.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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
Published2012
Admission routes1
Has abstractyes

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