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FMR1 alleles in Tasmania: a screening study of the special educational needs population

2004· article· en· W1483396689 on OpenAlexaff
Mitchell Rj, JJA Holden, C Zhang, Yvette Curlis, HR Slater, Trent Burgess, KC Kirkby, A Carmichael, KD Heading, Danuta Z. Loesch

Bibliographic record

VenueClinical Genetics · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsFMR1AlleleGeneticsFragile X syndromeBiologyPopulationAllele frequencyHaplotypeFragile xDemographyGene

Abstract

fetched live from OpenAlex

The distribution of fragile X mental retardation-1 (FMR1) allele categories, classified by the number of CGG repeats, in the population of Tasmania was investigated in 1253 males with special educational needs (SEN). The frequencies of these FMR1 categories were compared with those seen in controls as represented by 578 consecutive male births. The initial screening was based on polymerase chain reaction analysis of dried blood spots. Inconclusive results were verified by Southern analysis of a venous blood sample. The frequencies of common FMR1 alleles in both samples, and of grey zone alleles in the controls, were similar to those in other Caucasian populations. Consistent with earlier reports, we found some (although insignificant) increase of grey zone alleles in SEN subjects compared with controls. The frequencies of predisposing flanking haplotypes among grey zone males FMR1 alleles were similar to those seen in other Caucasian SEN samples. Contrary to expectation, given the normal frequency of grey zone alleles, no premutation (PM) or full mutation (FM) allele was detected in either sample, with only 15 fragile X families diagnosed through routine clinical admissions registered in Tasmania up to 2002. An explanation of this discrepancy could be that the C19th founders of Tasmania carried few PM or FM alleles. The eight to ten generations since white settlement of Tasmania has been insufficient time for susceptible grey zone alleles to evolve into the larger expansions.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.328
Teacher spread0.294 · 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 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".

Quick stats

Citations21
Published2004
Admission routes1
Has abstractyes

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