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Record W2943634270 · doi:10.1093/jxb/erz205

Growth and biomechanics of shoot organs

2019· review· en· W2943634270 on OpenAlexafffund
Emilie Echevin, Constance Le Gloanec, Nikolina Skowrońska, Anne‐Lise Routier‐Kierzkowska, Agata Burian, Daniel Kierzkowski

Bibliographic record

VenueJournal of Experimental Botany · 2019
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaNarodowym Centrum Nauki
KeywordsMorphogenesisBiologyBiomechanicsDevelopmental biologyPlant growthNeuroscienceEvolutionary biologyCell biologyAnatomyBotanyGenetics

Abstract

fetched live from OpenAlex

Plant organs arise through complex interactions between biological and physical factors that control morphogenesis. While there has been tremendous progress in the understanding of the genetics behind development, we know much less about how mechanical forces control growth in plants. In recent years, new multidisciplinary research combining genetics, live-imaging, physics, and computational modeling has begun to fill this gap by revealing the crucial role of biomechanics in the establishment of plant organs. In this review, we provide an overview of our current understanding of growth during initiation, patterning, and expansion of shoot lateral organs. We discuss how growth is controlled by physical forces, and how mechanical stresses generated during growth can control morphogenesis at the level of both cells and tissues. Understanding the mechanical basis of growth and morphogenesis in plants is in its early days, and many puzzling facts are yet to be deciphered.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.059
GPT teacher head0.324
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations44
Published2019
Admission routes2
Has abstractyes

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