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Record W2163185361 · doi:10.1093/jhered/esm036

Agouti Sequence Polymorphisms in Coyotes, Wolves and Dogs Suggest Hybridization

2007· article· en· W2163185361 on OpenAlexaffabout
S. M. Schmutz, T. G. Berryere, Jodi Lynn Barta, K. D. Reddick, Josef K. Schmutz

Bibliographic record

VenueJournal of Heredity · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsMcMaster UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsBiologyExonGeneticsCoding regionAllelePolymorphism (computer science)CoatPhenotypeGeneEcology

Abstract

fetched live from OpenAlex

Domestic dogs have been shown to have multiple alleles of the Agouti Signal Peptide (ASIP) in exon 4 and we wished to determine the level of polymorphism in the common wild canids of Canada, wolves and coyotes, in comparison. All Canadian coyotes and most wolves have banded hairs. The ASIP coding sequence of the wolf did not vary from the domestic dog but one variant was detected in exon 4 of coyotes that did not alter the arginine at this position. Two other differences were found in the sequence flanking exon 4 of coyotes compared with the 45 dogs and 1 wolf. The coyotes also demonstrated a relatively common polymorphism in the 3' UTR sequence that could be used for population studies. One of the ASIP alleles (R96C) in domestic dogs causes a solid black coat color in homozygotes. Although some wolves are melanistic, this phenotype does not appear to be caused by this same mutation. However, one wolf, potentially a dog-wolf hybrid or descendant thereof, was heterozygous for this allele. Likewise 2 coyotes, potentially dog-coyote or wolf-coyote hybrid descendants, were heterozygous for the several polymorphisms in and flanking exon 4. We could conclude that these were coyote-dog hybrids because both were heterozygous for 2 mutations causing fawn coat color in dogs.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.270

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 head0.024
GPT teacher head0.345
Teacher spread0.321 · 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 designBench or experimental
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

Citations26
Published2007
Admission routes2
Has abstractyes

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