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Record W1918196165 · doi:10.1139/cjb-2012-0227

Phenotypic plasticity in mating-system traits in the annual <i>Collinsia verna</i>

2013· article· en· W1918196165 on OpenAlexvenueno aff
Rachel B. Spigler, Susan Kalisz

Bibliographic record

VenueBotany · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsnot available
FundersUniversity of PittsburghNational Science Foundation
KeywordsBiologySelfingAbiotic componentPhenotypic plasticityMatingMating systemGrowing seasonTraitEcologyPopulation

Abstract

fetched live from OpenAlex

Variation in abiotic factors can influence the selective advantage of selfing and expression of the mating system if mating-system modifier traits are phenotypically plastic. However, relative to biotic factors, the role of abiotic conditions in driving variation in and evolution of plant mating systems is rarely addressed. We use an experimental approach to evaluate the extent to which genetic and environmental variation influence the expression of mating-system traits in the annual Collinsia verna. We subjected families to two environmental treatments in the greenhouse that varied in light and water availability, simulating natural and short flowering-season conditions, and examined the following: autonomous fruit set, flower number, flower size, rate of anther dehiscence, floral longevity, and timing of selfing. Our results demonstrate plasticity in nearly all traits examined. Compared with natural-season conditions, plants under short-season conditions produced fewer, smaller flowers and selfed approximately one day later due to slower anther dehiscence rates. Autonomous fruit set was similar across treatments, but there was genetic variation for plasticity in this important trait. Further, we show genetic variation in autonomous fruit set, timing of selfing, and flower number and size. Given the effects of global climate change on the duration of growing season, our results suggest that plasticity in mating-system traits will affect mating-system variation and, thus, opportunities for 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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.368

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 head0.210
Teacher spread0.202 · 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 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

Citations15
Published2013
Admission routes1
Has abstractyes

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