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Record W2077954840 · doi:10.2980/18-4-3422

Plant trait-mediated interactions between early and late herbivores on common figwort ( <i>Scrophularia nodosa</i> ) and effects on plant seed set

2011· article· en· W2077954840 on OpenAlexvenueno aff
Peter A. Hambäck, Johan P. Dahlgren, Petter Andersson, Sonja G. Rabasa, Riccardo Bommarco, Johan Ehrlén

Bibliographic record

VenueEcoscience · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyHerbivoreMeristemGrowing seasonWeevilBotanyPhenologyPlant tolerance to herbivoryCurculionidaeAgronomyShoot

Abstract

fetched live from OpenAlex

This study examined the interactive effects of early and late season herbivory on the growth and reproductive output of figwort (Scrophularia nodosa). The early season herbivore is a pentatomid bug that feeds on and kills the apical meristem, while the late season herbivores are 2 weevil species and a sawfly that all feed on leaves and flowers. The direct effect of early season meristem damage on plant reproduction was quite limited, although meristem damage did cause increased branching. This change in plant morphology may entail that early season herbivores have profound indirect effects on plant reproduction by affecting the abundance of and damage caused by late season herbivores. Comparisons of plants with and without early season meristem damage, natural and artificial, also suggest that plants with meristem damage are significantly shorter throughout most of the summer and receive less damage late in season. However, the reduced damage translated to increased flowering but not to increased fruit production, suggesting that the plants were able to compensate for late season damage. In the end, and despite damage, figwort was well able to tolerate the observed meristem and leaf damage.

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 score0.530
Threshold uncertainty score0.262

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 head0.024
GPT teacher head0.211
Teacher spread0.187 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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