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Record W2171667994 · doi:10.1007/s10897-013-9615-1

Large Normal and Intermediate Alleles in the Context of SCA2 Prenatal Diagnosis

2013· article· en· W2171667994 on OpenAlexaff
Tania Cruz Mariño, José Miguel Laffita‐Mesa, Yanetza González-Zaldívar, Miguel Velazquez‐Santos, Raúl Aguilera‐Rodríguez, Annelié Estupiñán‐Rodríguez, Yaimé Vázquez‐Mojena, Patrick MacLeod, Milena Paneque, Luis Velázquez‐Pérez

Bibliographic record

VenueJournal of Genetic Counseling · 2013
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGenetic counselingAllelePredictive testingGeneticsContext (archaeology)Spinocerebellar ataxiaMendelian inheritancePrenatal diagnosisTrinucleotide repeat expansionBiologyMedicineGenePregnancyFetus

Abstract

fetched live from OpenAlex

In 2001 a program for predictive testing of Spinocerebellar Ataxia type 2 was developed in Cuba, based on the detection of an abnormal CAG trinucleotide repeat expansion in the ATXN2 gene. A descriptive study was designed to assess the implications of ATXN2 large normal and intermediate alleles in the context of the SCA2 Prenatal Diagnosis Program. Four clinical scenarios were selected based upon the behaviour of large normal and intermediate alleles when passing from one generation to the next, showing expansions, contractions, or stability in the CAG repeat size. In some populations, traditional Mendelian risk figures of 0 % or 50 % may not be applicable due to the high frequency of unstable large normal alleles. Couples with no family history of SCA2 may have a >0 % risk of having an affected offspring. Similarly, couples in which there is both an expanded and a large normal allele may have a recurrence risk >50 %. It is imperative that these issues be addressed with these couples during genetic counseling. These recurrence risks have to be carefully estimated in the presence of such alleles (particularly alleles ≥27 CAG repeats), carriers need to be aware of the potential risk for their descendants, and programs for prenatal diagnosis must be available for them.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2013
Admission routes1
Has abstractyes

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