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Record W1995728283 · doi:10.1139/b06-133

Inhibition fields for phyllotactic pattern formation: a simulation studyThis article is one of a selection of papers published on the Special Theme of Shoot Apical Meristems.

2006· article· en· W1995728283 on OpenAlexafffundvenue
Richard S. Smith, Cris Kuhlemeier, Przemysław Prusinkiewicz

Bibliographic record

VenueCanadian Journal of Botany · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsPhyllotaxisPrimordiumMeristemBiologyPattern formationSpiral (railway)Computer scienceEvolutionary biologyBotanyEngineeringShootMechanical engineering

Abstract

fetched live from OpenAlex

Most theories of phyllotaxis are based on the idea that the formation of new primordia is inhibited by the proximity of older primordia. Several mechanisms that could result in such an inhibition have been proposed, including mechanical interactions, diffusion of a chemical inhibitor, and signaling by actively transported substances. Despite the apparent diversity of these mechanisms, their pattern-generation properties can be captured in a unified manner by inhibition fields surrounding the existing primordia. In this paper, we introduce a class of fields that depend on both the spatial distribution and the age of previously formed primordia. Using current techniques to create geometrically realistic, growing apex surfaces, we show that such fields can robustly generate a wide range of spiral, multijugate, and whorled phyllotactic patterns and their transitions. The mathematical form of the inhibition fields suggests research directions for future studies of phyllotactic patterning mechanisms.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.230
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations61
Published2006
Admission routes3
Has abstractyes

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Same venueCanadian Journal of BotanySame topicPlant Molecular Biology ResearchFrench-language works237,207