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Record W2078201629 · doi:10.1139/b08-128

Establishment growth and bud-bank formation in <i>Epilobium angustifolium</i>: the effects of nutrient availability, plant injury, and environmental heterogeneity

2009· article· en· W2078201629 on OpenAlexvenueno aff
Jitka Klimešová, Adéla Pokorná, Leoš Klimeš

Bibliographic record

VenueBotany · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersAkademie Věd České RepublikyGrantová Agentura České Republiky
KeywordsBiologyNutrientMeristemBiomass (ecology)BotanyPrimordiumVegetative reproductionAgronomyHorticultureShootEcology

Abstract

fetched live from OpenAlex

Plant establishment is a risky phase of the plant life cycle because juvenile individuals cannot produce seeds and their vegetative regeneration is constrained by a lack of reserve meristems and carbon storage. On the other hand, conditions in the period following establishment, during establishment growth, affect the vegetative regeneration and clonal growth of the plant in the future. Bud-bank formation was studied in a root-sprouting clonal herb Epilobium angustifolium L. (= Chamaenerion angustifolium (L.) Scop.), a plant with root buds differing in size and number of leaf primordia, during establishment growth. We tested two hypotheses: (i) large and small buds differ in their response to stress and disturbance, and (ii) a heterogeneous soil environment does not affect bud-bank formation. We rejected both hypotheses because (i) the proportion of small buds was about 80% and was not affected by nutrient availability and substrate heterogeneity, and (ii) plants produced more buds per root biomass under conditions of nutrient shortage in both homogeneous and heterogeneous substrates, but the effect was masked by lower root biomass. Thus, bud production for the whole plant was not affected by either nutrient availability or soil heterogeneity and reached 20 to 100 buds per plant.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.296

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 head0.004
GPT teacher head0.198
Teacher spread0.193 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

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