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Record W2133214874 · doi:10.1139/cjb-2014-0169

Analysis of pollination neighbourhood size using spatial analysis of pollen and seed production in broadleaf cattail (<i>Typha latifolia</i>)

2014· article· en· W2133214874 on OpenAlexaffvenue
Jordan E. Ahee, Wendy E. Van Drunen, Marcel E. Dorken

Bibliographic record

VenueBotany · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsTrent University
Fundersnot available
KeywordsPollenBiologyPollinationSelfingBotanyBiological dispersalPopulation

Abstract

fetched live from OpenAlex

The size of pollination neighbourhoods has important consequences for mating patterns, seed production, gene flow, and patterns of genetic variation across populations. We examined the size of the pollination neighbourhood in a stand of a wind-pollinated clonal plant (Typha latifolia L.; broadleaf cattail) by evaluating spatial patterns of pollen production and seed set by individual shoots. We then simulated spatial patterns of pollen availability to investigate the shape of the pollen dispersal curve. We detected significant positive spatial autocorrelations in seed set over distances up to 5 m. This spatial variation in patterns of seed set appeared to be driven by the local availability of pollen: we found significant cross-correlations between pollen production and seed set over distances of approximately 2 m. The simulations supported this inference; simulated pollen dispersal curves fit observed patterns of seed set when ∼99% of pollen was assumed to disperse over distances less than 2 m. Together, these results indicate that the majority of pollination events occur within very close proximity of pollen sources in T. latifolia. Although within-shoot selfing has long been assumed to be a major pollination mode in T. latifolia, our data indicate that pollination events in the stand were more likely to have involved between-shoot pollination.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.023
GPT teacher head0.222
Teacher spread0.199 · 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

Citations35
Published2014
Admission routes2
Has abstractyes

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