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Record W3212272617 · doi:10.1139/cjb-2021-0038

Measurement of inbreeding depression in <i>Rhododendron kaempferi</i>: seed production, germination, juvenile survival, and growth

2021· article· en· W3212272617 on OpenAlexvenueno aff
Keigo Takahashi, Takao Itino

Bibliographic record

VenueBotany · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyInbreeding depressionSelfingOutcrossingPollinationPopulationGerminationHand-pollinationBotanyPollinatorHorticultureInbreedingPollen

Abstract

fetched live from OpenAlex

To understand the reproductive ecology of a plant species with both selfing and outcrossing reproductive systems, it is important to know how selfed individuals contribute to the maintenance of a population. Further, examination of the magnitude of inbreeding depression after pollination is essential for the accurate measurement of reproductive success. In this study, we investigated the characteristics of viable seeds and seedlings of Rhododendron kaempferi Planch. in a region where the bumblebee pollinator Bombus ardens Smith, 1879 are abundant. In a hand-pollination experiment, the fruit set from self-pollination was 32%, significantly lower than that from outcross-pollination (81%). The number of seeds per fruit from self-pollination was one sixth the number from outcross-pollination. However, the number of seeds per fruit was negatively correlated with the mass per seed. In addition, the germination rate was low when the seed mass was light. Although selfed seeds could germinate, 89% of the seedlings died within a year. The inbreeding depression coefficient one year after sowing was very high (0.89). These results indicate that R. kaempferi shows extremely strong selection for outcrossing but maintains a slight selfing potential in a natural population in central Japan.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.051
GPT teacher head0.222
Teacher spread0.171 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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