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Record W4401074649 · doi:10.1080/15592324.2024.2384243

Characterizing the role of endocarp <i>a</i> and <i>b</i> cells layers during pod (silique) development in Brassicaceae

2024· article· en· W4401074649 on OpenAlexafffund
Justin B. Nichol, Marcus A. Samuel

Bibliographic record

VenuePlant Signaling & Behavior · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSiliqueBrassicaceaeBiologyBrassicaArabidopsis thalianaBotanyArabidopsisBrassica carinataDehiscenceXylemCanolaMutantGeneGenetics

Abstract

fetched live from OpenAlex

The process of silique dehiscence is essential for the proper dispersal of seeds at the end of a dehiscent fruit plants lifecycle. Current research focuses on genetic manipulation to mitigate this process and enhance shatter tolerance in crop plants, which has significant economic implications. In this study, we have conducted a time-course analysis of cell patterning and development in valve tissues of Arabidopsis thaliana and closely related Triangle of U species (Brassica juncea, Brassica carinata, Brassica napus, Brassica rapa, and Brassica nigra) from Brassicaceae. The goal was to decipher the detailed temporal developmental patterns of the endocarp a and b cell layers of the valve, specifically their degradation and lignification respectively. Additionally, we propose a new classification system for the lignification of the endocarp a cell layer: L1 indicates the cell closest to the replum, with L2 and L3 representing the second and third cells, respectively, each numerical increment indicating lignified cells farther from the replum. Our findings provide a foundational framework absent in current literature, serving as an effective blueprint for future genomic work aimed at modifying valve structures to enhance agronomic traits, such as reducing fiber (lignin) or increasing shatter tolerance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.203

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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 designBench or experimental
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

Citations7
Published2024
Admission routes2
Has abstractyes

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