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Record W2095059307 · doi:10.3354/esr00291

Reproductive ecology of the western silvery aster Symphyotrichum sericeum in Canada

2010· article· en· W2095059307 on OpenAlexfundaboutno aff
D.B. Robson

Bibliographic record

VenueEndangered Species Research · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaGovernment of CanadaWorld Wildlife Fund
KeywordsBiologyForbCompetition (biology)BotanyInflorescencePredationEcologyGrassland

Abstract

fetched live from OpenAlex

Previous studies suggest that low seed production due to pollinator competition and seed predation may negatively affect the reproduction of the rare forb western silvery aster Symphyotrichum sericeum in Canada. Research was conducted to determine normal flower and seed production and the impact of seed predation, and to ascertain whether clipping surrounding vegetation and/or fertilizing with nitrogen stimulates flower and seed production in S. sericeum. Only 41% of all stems observed produced capitula, and less than 40% of the seeds in each capitulum were filled. Flower production was negatively correlated with percentage vascular plant cover and positively correlated with percentage cryptogamic cover. The main seed predator was a weevil (Anthonomus sp.) that destroyed about one-third of all capitula produced. None of the treatments applied (e.g. clipped, fertilized and clipped fertilized) significantly increased stem height, the percentage of flowering stems or seed production over the control; clipping actually decreased stem height. Fertilizing was the only treatment that showed some promise as it increased the number of capitula per flowering stem. Flower and seed production in S. sericeum may be facilitated by the presence of other species that modify the microenvironment. Low flower and seed production of plants in Canada is likely due to limited soil resources and pollen, and seed predation.

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 score0.492
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.260
Teacher spread0.183 · 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

Citations3
Published2010
Admission routes2
Has abstractyes

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