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Record W4389180351 · doi:10.1002/ajb2.16262

Gamete sex and elevation affect genetically based variation for unreduced gamete production in a mixed‐ploidy plant

2023· article· en· W4389180351 on OpenAlexafffund
S. E. DeVries, Paul Kron, Brian C. Husband

Bibliographic record

VenueAmerican Journal of Botany · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyGametePloidyVariation (astronomy)BotanyGeneticsGene

Abstract

fetched live from OpenAlex

PREMISE: Unreduced gametes are the primary mechanism of neopolyploid formation. Their production in diploid populations is arguably maladaptive, but the magnitude and patterns of genetically based variation maintained in natural populations are poorly understood. METHODS: We examined variation in male and female unreduced gamete production among plants from different elevations in fireweed, Chamerion angustifolium, grown in a common environment. Using seeds from three high-elevation and three low-elevation diploid populations in one study, and a single diploid population in another, we estimated realized rates of unreduced male (sperm) and female (egg) gamete production by reciprocally pollinating diploid and tetraploid plants and estimating the incidence of tetraploid seeds using flow cytometry. RESULTS: Unreduced gamete frequencies per plant were similar in the two studies (0.12% vs. 0.08%). High-elevation populations had a greater percentage of fruit with seeds from unreduced gametes, but a lower percentage of seeds per fruit than low-elevation populations. Female unreduced gamete frequencies differed among elevations, but male frequencies did not, and the gamete sexes were not correlated at the plant level. CONCLUSIONS: We conclude that genetically based variation for unreduced gametes is maintained within and among natural populations, despite their fitness disadvantages, suggesting that local selection may be ineffective at purging them under some conditions.

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)0.001
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 score0.978
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.232
Teacher spread0.199 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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