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Record W2065563746 · doi:10.1086/378902

Frequency‐Dependent Inbreeding Depression in <i>Amsinckia</i>

2003· article· en· W2065563746 on OpenAlexafffund
Pierre‐Olivier Cheptou, Daniel J. Schoen

Bibliographic record

VenueThe American Naturalist · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInbreeding depressionOutcrossingSelfingBiologyInbreedingCompetition (biology)Mating systemMatingInbred strainBotanyZoologyEvolutionary biologyEcologyGeneticsPopulationPollenDemography

Abstract

fetched live from OpenAlex

If the competitive ability of plants produced by self-pollination differs from that of plants derived by outcrossing, then the magnitude of inbreeding depression may be influenced by the composition of the competitive environment (i.e., the frequency of plants that have arisen from selfing and outcrossing in the neighborhood of "target" plants in which inbreeding depression is expressed). Here, we report the results of experiments designed to examine whether inbreeding depression is influenced by the frequency of inbred plants in the competitive neighborhood. Two species of the annual plant genus Amsinckia were studied, one a near-complete selfer (Amsinckia gloriosa) and the other a partial outcrosser (Amsinckia douglasiana). Competition experiments were conducted in artificial stands composed of different mixtures of inbred and outbred progeny. The fitnesses of progeny were found to be significantly influenced by the composition of the competing neighborhood. The fitness of target plants, however, did not vary monotonically with the frequency of inbred plants in the neighborhood. Rather, for A. gloriosa, maximum performance was observed when there was an intermediate frequency of inbred neighbors. For A. douglasiana, the opposite pattern was found. The results suggest that competition among progeny has the potential to play a role in the selection of self-fertilization and possibly in the maintenance of mixed mating systems.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.398

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 head0.028
GPT teacher head0.223
Teacher spread0.195 · 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

Citations27
Published2003
Admission routes2
Has abstractyes

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