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CORRELATED EVOLUTION OF SEXUAL SYSTEM AND LIFE-HISTORY TRAITS IN MOSSES

2009· article· en· W2104746817 on OpenAlexafffund
Monique Crawford, Linley K. Jesson, P. J. Garnock‐Jones

Bibliographic record

VenueEvolution · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBryophyte Studies and Records
Canadian institutionsUniversity of New Brunswick
FundersMarsden FundNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyAsexual reproductionSexual reproductionBiological dispersalApomixisPhylogenetic treeTraitEvolutionary biologyLife history theorySporePhylogeneticsPhylogenetic comparative methodsReproductionEvolution of sexual reproductionPloidyLife historyEcologyBotanyGeneticsGeneDemography

Abstract

fetched live from OpenAlex

In mosses, separate and combined sexes are evolutionarily labile, yet factors selecting for this variation are unknown. In this study, we investigate phylogenetic correlations between sexual system and five life-history traits (asexual reproduction, chromosome number, gametophore length, spore size, and seta length). We assigned states to species on a large-scale phylogeny of mosses and used maximum likelihood analyses to test for the correlations and investigate the sequence of trait acquisition. Mosses in lineages with separate sexes were significantly more likely to be large, whereas those in lineages with combined sexes had higher chromosome numbers. Moreover, evolutionary transitions to separate sexes were more likely to occur in lineages with small spores. There was no support for a correlation between asexual reproduction and separate sexes. These results suggest that sexual system evolution is influenced by traits affecting mate availability and the dispersal of gametes and spores, and provides evidence for the existence of syndromes of life-history traits in mosses.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.180
Teacher spread0.169 · 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 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

Citations71
Published2009
Admission routes2
Has abstractyes

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