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CCMG guidelines: prenatal and postnatal diagnostic testing for uniparental disomy

2010· article· en· W2117476997 on OpenAlexaffabout
AJ Dawson, Judy Chernos, Jean McGowan‐Jordan, Josée N. Lavoie, Shashirekha Shetty, Michelle Steinraths, J.C. Wang, Jie Xu

Bibliographic record

VenueClinical Genetics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsLondon Health Sciences CentreMcMaster UniversityVictoria General HospitalMontreal Children's HospitalChildren's Hospital of Eastern OntarioAlberta Children's HospitalDiagnostic Services Manitoba
Fundersnot available
KeywordsUniparental disomyGenetic testingPrenatal diagnosisGuidelineMedicineDiagnostic testGenetic counselingMedical geneticsGeneticsFamily medicinePediatricsBiologyPregnancyChromosomeKaryotypePathology

Abstract

fetched live from OpenAlex

Dawson AJ, Chernos J, McGowan-Jordan J, Lavoie J, Shetty S, Steinraths M, Wang J-C, Xu J. CCMG guidelines: prenatal and postnatal diagnostic testing for uniparental disomy. The aim of this statement is to provide clinicians, cytogeneticists and molecular geneticists of the Canadian College of Medical Geneticists (CCMG) a comprehensive review of the role of UPD in constitutional genetic diagnosis and to provide a guideline as to when investigation for UPD is recommended. Members of the CCMG Cytogenetics, Molecular Genetics, Clinical Practice, and Prenatal Diagnosis committees reviewed the relevant literature on uniparental disomy (UPD) in constitutional genetic diagnosis (May 2010). Guidelines were developed for UPD testing in Canada. The guidelines were circulated for comment to the CCMG members at large and following appropriate modification, approved by the CCMG Board of Directors (July 2010).

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)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0080.005

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 head0.066
GPT teacher head0.377
Teacher spread0.312 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations65
Published2010
Admission routes2
Has abstractyes

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