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Record W1827081112 · doi:10.1139/cjb-2013-0324

Variations in the effects of local foliar damage on life span of individual leaves of downy birch (<i>Betula pubescens</i>)

2014· article· en· W1827081112 on OpenAlexvenueno aff
Mikhail V. Kozlov, Elena L. Zvereva

Bibliographic record

VenueBotany · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
Fundersnot available
KeywordsHerbivoreBiologyAbscissionBetula pubescensBotanyBetulaceaeLife spanGuildInsectHorticultureEcology

Abstract

fetched live from OpenAlex

Although the premature abscission of leaves damaged by herbivores has been discovered decades ago, the reduction in leaf life span caused by herbivory remains poorly documented, and the sources of variation in the magnitude of this effect have only rarely been studied. We aimed at exploring the effects of several herbivore species (at their background densities) and simulated herbivory on the leaf life span of downy birch, Betula pubescens Ehrh. Leaves damaged by herbivores abscised on average 12.6 days earlier and punched leaves 3.5 days earlier than the intact leaves of the control shoots. Different herbivores reduced the life span of the birch leaves from 0% to 27% depending on the intensity and timing of the damage but not on the insect feeding guild. The reduction in leaf life span was greater when the damage was imposed on expanding and growing leaves compared with mature leaves. However, the effect of herbivore species remained significant after accounting for intensity and timing of damage. This fact, together with greater reduction in leaf life span due to natural herbivory compared with mechanical damage, indicates that premature abscission in response to injury is considerably enhanced by insect-specific elicitors.

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 score0.968
Threshold uncertainty score0.108

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 head0.009
GPT teacher head0.205
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

Citations10
Published2014
Admission routes1
Has abstractyes

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