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The Ecology of Mating and Its Evolutionary Consequences in Seed Plants

2017· article· en· W2616100914 on OpenAlexafffund
Spencer C. H. Barrett, Lawrence D. Harder

Bibliographic record

VenueAnnual Review of Ecology Evolution and Systematics · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of CalgaryUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyOutcrossingMating systemMatingSelfingEcologyOutbreeding depressionOvuleEvolutionary ecologyPollen tubeContext (archaeology)PollinationPollinatorEvolutionary biologyInbreedingPollenPopulation

Abstract

fetched live from OpenAlex

Mating in seed plants arises from interactions between plant traits and the environmental and demographic context in which individuals reside. These interactions commonly cause nonrandom mating, including selfing and promiscuous outcrossing within local neighborhoods. Shared features of seed plants, specifically immobility, hermaphroditism, and modularity, shape the essential character of mating mediated by animals, wind, and water. In addition, diverse floral strategies promote cross- and self-mating, depending on environmental circumstances. Extrinsic ecological factors influence all stages of the mating process—pollination, pollen-tube growth, ovule fertilization—as well as seed development, determining offspring quantity and quality. Traditionally, measures of plant mating systems have focused on a single axis of variation, the maternal outcrossing rate. Instead, we argue for an expanded perspective encompassing mating portfolios, which include all offspring to which individuals contribute genetically as maternal or paternal parents. This approach should expose key ecological determinants of mating-system variation and their evolutionary consequences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.273
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations201
Published2017
Admission routes2
Has abstractyes

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