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Record W2519126396 · doi:10.1038/npjgenmed.2016.31

The importance of copy number variation in congenital heart disease

2016· article· en· W2519126396 on OpenAlexafffund
Gregory Costain, Candice K. Silversides, Anne S. Bassett

Bibliographic record

Venuenpj Genomic Medicine · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsUniversity Health NetworkHospital for Sick ChildrenMount Sinai HospitalCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsCopy-number variationGenetic architectureBiologyGeneticsHeart diseaseGenomeChromosomeDiseaseGenetic variationHuman genomeMicroarrayGeneComputational biologyMedicineQuantitative trait locusPathologyGene expression

Abstract

fetched live from OpenAlex

Abstract Congenital heart disease (CHD) is the most common class of major malformations in humans. The historical association with large chromosomal abnormalities foreshadowed the role of submicroscopic rare copy number variations (CNVs) as important genetic causes of CHD. Recent studies have provided robust evidence for these structural variants as genome-wide contributors to all forms of CHD, including CHD that appears isolated without extra-cardiac features. Overall, a CNV-related molecular diagnosis can be made in up to one in eight patients with CHD. These include de novo and inherited variants at established (chromosome 22q11.2), emerging (chromosome 1q21.1), and novel loci across the genome. Variable expression of rare CNVs provides support for the notion of a genetic spectrum of CHD that crosses traditional anatomic classification boundaries. Clinical genetic testing using genome-wide technologies (e.g., chromosomal microarray analysis) is increasingly employed in prenatal, paediatric and adult settings. CNV discoveries in CHD have translated to changes to clinical management, prognostication and genetic counselling. The convergence of findings at individual gene and at pathway levels is shedding light on the mechanisms that govern human cardiac morphogenesis. These clinical and research advances are helping to inform whole-genome sequencing, the next logical step in delineating the genetic architecture of CHD.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.224

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 head0.012
GPT teacher head0.297
Teacher spread0.285 · 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

Citations92
Published2016
Admission routes2
Has abstractyes

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