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Genome‐wide cross‐amplification of domestic sheep microsatellites in bighorn sheep and mountain goats

2009· article· en· W2087828610 on OpenAlexaff
Jocelyn Poissant, Aaron B. A. Shafer, Corey S. Davis, Julien Mainguy, John T. Hogg, Steve Côté, David W. Coltman

Bibliographic record

VenueMolecular Ecology Resources · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversité LavalCenter for Northern StudiesUniversity of Alberta
Fundersnot available
KeywordsBiologyMicrosatelliteGenomeOvis canadensisGeneticsZoologyEvolutionary biologyGeneAllele

Abstract

fetched live from OpenAlex

We tested for cross-species amplification of microsatellite loci located throughout the domestic sheep (Ovis aries) genome in two north American mountain ungulates (bighorn sheep, Ovis canadensis, and mountain goats, Oreamnos americanus). We identified 247 new polymorphic markers in bighorn sheep (≥ 3 alleles in one of two study populations) and 149 in mountain goats (≥ 2 alleles in a single study population) using 648 and 576 primer pairs, respectively. Our efforts increased the number of available polymorphic microsatellite markers to 327 for bighorn sheep and 180 for mountain goats. The average distance between successive polymorphic bighorn sheep and mountain goat markers inferred from the Australian domestic sheep genome linkage map (mean ± 1 SD) was 11.9 ± 9.2 and 15.8 ± 13.8 centimorgans, respectively. The development of genomic resources in these wildlife species enables future studies of the genetic architecture of trait variation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 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

Citations25
Published2009
Admission routes1
Has abstractyes

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