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Record W2111374582 · doi:10.1126/science.1107891

The Effects of Artificial Selection on the Maize Genome

2005· article· en· W2111374582 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

VenueScience · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsYork University
Fundersnot available
KeywordsDomesticationBiologyGenomeGeneSelection (genetic algorithm)PolygeneZea maysGeneticsQuantitative trait locusCandidate genePopulationTraitPhenotypeEvolutionary biologyAgronomy

Abstract

fetched live from OpenAlex

Domestication promotes rapid phenotypic evolution through artificial selection. We investigated the genetic history by which the wild grass teosinte (Zea mays ssp. parviglumis) was domesticated into modern maize (Z. mays ssp. mays). Analysis of single-nucleotide polymorphisms in 774 genes indicates that 2 to 4% of these genes experienced artificial selection. The remaining genes retain evidence of a population bottleneck associated with domestication. Candidate selected genes with putative function in plant growth are clustered near quantitative trait loci that contribute to phenotypic differences between maize and teosinte. If we assume that our sample of genes is representative, approximately 1200 genes throughout the maize genome have been affected by artificial selection.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.266

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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