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Record W2156402967 · doi:10.1139/cjb-2013-0011

Growth temperature affects inflorescence architecture in<i>Arabidopsis thaliana</i>

2013· article· en· W2156402967 on OpenAlexafffundvenue
Marlène Antoun, François Ouellet

Bibliographic record

VenueBotany · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInflorescenceBiologyPlant stemBoltingRosette (schizont appearance)Apical dominanceMeristemBotanyVegetative reproductionArabidopsis thalianaArabidopsisElongationHorticultureCropAgronomyShootMutant

Abstract

fetched live from OpenAlex

Plants adjust their growth and development to ensure survival under adverse environmental conditions. Nonoptimal growth temperatures can have a major impact on biomass and crop yield. A detailed phenotypic analysis (number and length of rosette and cauline branches, flowers, and buds) in Arabidopsis thaliana revealed that growth temperatures below (12 and 17 °C) and above (27 and 32 °C) the control 22 °C affect branching and flowering. The elongation of internodes on the main stem and of primary branches at cauline leaves is reduced at lower temperatures and increased at higher temperatures. Similar results are observed in plants treated before or after bolting. Our data therefore indicate that plants that have transitioned to the reproductive stage before treatment are slightly less affected by temperature variations than plants that are in their vegetative stage. Our results also suggest that plants need to reach a maximum height (internodes length) before they begin forming floral meristems and that this “maximum height” is dependent on the growth temperature. Plants grown at 17 °C show a slightly reduced branching, while those at 27 °C show increased branching. This suggests that apical dominance is a temperature-dependent phenomenon. This is, to our knowledge, the first extensive analysis of the effect of temperature on Arabidopsis inflorescence development.

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 score0.903
Threshold uncertainty score0.348

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 head0.008
GPT teacher head0.206
Teacher spread0.197 · 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

Citations16
Published2013
Admission routes3
Has abstractyes

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