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Record W2111629801 · doi:10.1093/molbev/msu070

Population Variation Revealed High-Altitude Adaptation of Tibetan Mastiffs

2014· article· en· W2111629801 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Biology and Evolution · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsDiabetes CanadaUniversity of Toronto
FundersNational Science Foundation
KeywordsBiologyAdaptation (eye)Single-nucleotide polymorphismNucleotide diversityEvolutionary biologyGenetic diversityGenetic variationPopulationGeneticsGeneBalancing selectionHaplotypeGenotype

Abstract

fetched live from OpenAlex

With the assistance of their human companions, dogs have dispersed into new environments during the expansion of human civilization. Tibetan Mastiff (TM), a native of the Tibetan Plateau, was derived from the domesticated Chinese native dog and, like Tibetans, has adapted to the extreme environment of high altitude. Here, we genotyped genome-wide single-nucleotide polymorphisms (SNPs) from 32 TMs and compared them with SNPs from 20 Chinese native dogs and 14 gray wolves (Canis lupus). We identified 16 genes with signals of positive selection in the TM, with 12 of these candidate genes associated with functions that have roles in adaptation to high-altitude adaptation, such as EPAS1, SIRT7, PLXNA4, and MAFG that have roles in responses to hypoxia. This study provides important information on the genetic diversity of the TM and potential mechanisms for adaptation to hypoxia.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.453

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 head0.005
GPT teacher head0.232
Teacher spread0.227 · 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