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Record W2145685931 · doi:10.1093/jhered/esi072

Mutant Allele Frequencies in Domestic Cat Populations in Arkansas and Tennessee

2005· article· en· W2145685931 on OpenAlexaboutno aff
Joseph Mark Shostell, J. Staudinger, Manuel Ruiz‐García

Bibliographic record

VenueJournal of Heredity · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersNational Eye InstituteUniversity of Central Arkansas
KeywordsBiologyAllele frequencyAlleleIsolation by distancePopulationPopulation geneticsZoologyDemographyGeneticsGeneMicrosatellite

Abstract

fetched live from OpenAlex

We conducted surveys of mutant allele frequencies of four cat populations in Arkansas and Tennessee during 2002. Our calculations and analyses support that Southwestern cat populations were relatively more genetically similar to each other than compared to cat populations in other areas of North America. However, the cat population of Fort Smith is slightly different from the other cat populations studied in the Southwestern United States. Although there is a clear significant spatial geographic pattern for many mutant coat allele frequencies in the United States and Canada cat populations (d, l, S, and W), our results revealed that there is not a significant isolation-by-distance model affecting these cat populations. Our data also support the historical migration hypothesis because our calculated allele frequencies were genetically similar to cat populations located in ancestral areas of Europe. Different phenograms, including new European cat genetic profiles, showed that the Southwestern cat populations studied are of a clear British origin. Therefore, migration routes of early Arkansas and Tennessee settlers help explain the similarities of allele frequencies among domestic cat populations.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.997

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 head0.033
GPT teacher head0.295
Teacher spread0.262 · 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

Citations8
Published2005
Admission routes1
Has abstractyes

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