MétaCan
Menu
Back to cohort
Record W2131228867 · doi:10.1111/jeb.12741

Pollen limitation and its influence on natural selection through seed set

2015· article· en· W2131228867 on OpenAlexafffundabout
Magdalena P. Bartkowska, Mark O. Johnston

Bibliographic record

VenueJournal of Evolutionary Biology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyPollenPollinatorSelection (genetic algorithm)Natural selectionTraitPopulationEcologyZoologyPollinationDemographyMachine learning

Abstract

fetched live from OpenAlex

Stronger pollen limitation should increase competition among plants, leading to stronger selection on traits important for pollen receipt. The few explicit tests of this hypothesis, however, have provided conflicting support. Using the arithmetic relationship between these two quantities, we show that increased pollen limitation will automatically result in stronger selection (all else equal) although other factors can alter selection independently of pollen limitation. We then tested the hypothesis using two approaches. First, we analysed the published studies containing information on both pollen limitation and selection. Second, we explored how natural selection measured in one Ontario population of Lobelia cardinalis over 3 years and two Michigan populations in 1 year relates to pollen limitation. For the Ontario population, we also explored whether pollinator-mediated selection is related to pollen limitation. Consistent with the hypothesis, we found an overall positive relationship between selection strength and pollen limitation both among species and within L. cardinalis. Unexpectedly, this relationship was found even for vegetative traits among species, and was not found in L. cardinalis for pollinator-mediated selection on nearly all trait types.

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 score0.632
Threshold uncertainty score0.103

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 head0.077
GPT teacher head0.264
Teacher spread0.186 · 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

Citations28
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Evolutionary BiologySame topicPlant and animal studiesFrench-language works237,207