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Record W2141171342 · doi:10.1199/tab.0126

Embryogenesis: Pattern Formation from a Single Cell

2009· article· en· W2141171342 on OpenAlexaff
Arnaud Capron, Steven P. Chatfield, Nicholas J. Provart, Thomas Berleth

Bibliographic record

VenueThe Arabidopsis Book · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of Toronto
FundersCompany of BiologistsAmerican Association for the Advancement of Science
KeywordsMulticellular organismBiologyArabidopsisEmbryoEmbryogenesisCell biologyBotanyEmbryonic stem cellSomatic embryogenesisShootEvolutionary biologyCellGeneticsGene

Abstract

fetched live from OpenAlex

During embryogenesis a single cell gives rise to a functional multicellular organism. In higher plants, as in many other multicellular systems, essential architectural features, such as body axes and major tissue layers are established early in embryogenesis and serve as a positional framework for subsequent pattern elaboration. In Arabidopsis, the apicalbasal axis and the radial pattern of tissues wrapped around it are already recognizable in young embryos of only about a hundred cells in size. This early axial pattern seems to provide a coordinate system for the embryonic initiation of shoot and root. Findings from genetic studies in Arabidopsis are revealing molecular mechanisms underlying the initial establishment of the axial core pattern and its subsequent elaboration into functional shoots and roots. The genetic programs operating in the early embryo organize functional cell patterns rapidly and reproducibly from minimal cell numbers. Understanding their molecular details could therefore greatly expand our ability to generate plant body patterns de novo, with important implications for plant breeding and biotechnology.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.007

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 head0.023
GPT teacher head0.212
Teacher spread0.189 · 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 designTheoretical or conceptual
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

Citations182
Published2009
Admission routes1
Has abstractyes

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