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Record W2043082221 · doi:10.1111/pbr.12245

Sexual hybridization between <i>Capsella bursa‐pastoris</i> (L.) Medik (♀) and <i>Camelina sativa</i> (L.) Crantz (♂) (Brassicaceae)

2015· article· en· W2043082221 on OpenAlexafffundabout
Sara L. Martin, Connie A. Sauder, Tracey James, Kyle W. Cheung, Fakhria M. Razeq, Paul Kron, Linda M. Hall

Bibliographic record

VenuePlant Breeding · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsUniversity of AlbertaUniversity of GuelphAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaUniversity of Warwick
KeywordsBiologyHybridPollenBotanyCamelinaCamelina sativaPollinationEmasculationSelfingOutcrossingAgronomyPopulationCrop

Abstract

fetched live from OpenAlex

Abstract The development of transgenic oilseed Camelina sativa (2n = 40) and the potential for hybridization with its weedy relative Capsella bursa‐pastoris (2n = 36) necessitates a careful evaluation of the reproductive compatibility between the species. Here, we conducted over 1800 crosses (emasculation and manual pollination) to examine the ability of 10 Canadian C. bursa‐pastoris (♀) accessions to hybridize with five accessions of C. sativa (♂). Seven hybrids were confirmed among 586 putative hybrids screened with species‐specific markers, indicating a hybridization rate of 1.5 hybrids per 10 000 ovules pollinated. All seven hybrids had intermediate DNA content compared to their parents, were morphologically distinct, had low (1.9%) pollen fertility and failed to produce selfed or backcrossed seed. Given the abundance of C. bursa‐pastoris along field margins, hybrids will likely be generated in the wild, but they will be unable to establish lineages unless fertility is restored. The large number of crosses and the diversity captured by the use of multiple accessions resulted in strong statistical power and a high degree of confidence in the estimated hybridization rate.

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 score0.497
Threshold uncertainty score0.336

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 head0.042
GPT teacher head0.219
Teacher spread0.177 · 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

Citations24
Published2015
Admission routes3
Has abstractyes

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