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Record W1710646799 · doi:10.1002/047001153x.g103106

Imprinting and epigenetic inheritance in human disease

2005· other· en· W1710646799 on OpenAlexaff
Constantin Polychronakos

Bibliographic record

VenueEncyclopedia of Genetics, Genomics, Proteomics and Bioinformatics · 2005
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsImprinting (psychology)Genomic imprintingEpigeneticsGeneticsBiologyPhenotypeInheritance (genetic algorithm)Gene silencingGeneDiseaseDNA methylationGene expressionMedicine

Abstract

fetched live from OpenAlex

Abstract The silencing of either the paternal or the maternal copy of the few human genes that are subject to parental imprinting may contribute to genetic disease or modify its inheritance pattern. Disruption of the normal process of imprinting may result in double gene dosage if both copies are expressed or in a null phenotype if neither is. When normally imposed, imprinting can play a role in disease by leaving only one of the two copies to be inactivated by mutation. This introductory review explains the various mechanisms and gives examples of the best‐understood diseases where imprinting plays an important role.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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.

Study designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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