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Record W4233469836 · doi:10.1051/gse:2003033

Analysis of <i>PDE6D</i> and <i>PDE6G</i> genes for generalised progressive retinal atrophy (gPRA) mutations in dogs

2003· article· en· W4233469836 on OpenAlexaboutno aff
Gabriele Dekomien

Bibliographic record

VenueGenetics Selection Evolution · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsExonBiologyGeneticsGeneIntronSNPRetinal degenerationSingle-nucleotide polymorphismMutationCoding regionAtrophyGenotype

Abstract

fetched live from OpenAlex

The δ and γ subunits of the cGMP-phosphodiesterase ( PDE6D , PDE6G ) genes were screened in order to identify mutations causing generalised progressive retinal atrophy (gPRA) in dogs. In the PDE6D gene, single nucleotide polymorphisms (SNP) were observed in exon 4, in introns 2 and 3 and in the 3' untranslated region (UTR) of different dog breeds. In the coding region of the PDE6G gene, exclusively healthy Labrador Retrievers showed an A → G transition in exon 4 without amino acid exchange. SNP were also observed in introns 1 and 2 in different dog breeds. The different SNP were used as intragenic markers to investigate the involvement of both genes in gPRA. The informative substitutions allowed us to exclude mutations in the PDE6D and PDE6G genes as causing retinal degeneration in 15 of the 22 dog breeds with presumed autosomal recessively transmitted (ar) gPRA.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.244
Teacher spread0.238 · 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 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

Citations0
Published2003
Admission routes1
Has abstractyes

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