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Record W2025266886 · doi:10.2298/abs1104037m

The effects of tannic acid on the fitness-related traits of Lymantria dispar L. larvae

2011· article· en· W2025266886 on OpenAlexaff
Marija Mrdaković, Vesna Perić‐Mataruga, Larisa Ilijin, Milena Vlahović, Dajana Todorović, Vera Nenadović, Jelica Lazarević

Bibliographic record

VenueArchives of Biological Sciences · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsRobiniaBiologyTannic acidLarvaLymantria disparPopulationPhenotypic plasticityGypsy mothPupaHeritabilityZoologyHost (biology)BotanyInstarEcologyEvolutionary biologyDemography

Abstract

fetched live from OpenAlex

In this study we investigated the effects of tannic acid on fitness-related traits in gypsy moth larvae from two differently adapted populations. Thirty two full-sib families from oak (suitable host plant, Quercus population), and twenty six full-sib families from locust-tree (unsuitable host plant, Robinia population) forests were reared on artificial diets with or without a 5% tannic acid supplement. Tannic acid shortened the duration of larval development till the 4th instar in the Robinia population, and decreased the mass of larvae from both Quercus and Robinia populations. Local adaptation was not recorded for any of the examined traits. In general, regardless of population origin, genetic variation (broad-sense heritability) was higher in larvae fed on the diet containing tannic acid than in larvae fed on the control diet. Variability of phenotypic plasticity was significant for the examined traits, except for larval duration traits in Quercus larvae, pointing to the potential of gypsy moth larvae from both populations for the evolution of adaptive plastic responses to new environmental conditions and the presence of stressors. Genetic correlations between the environments were positive and significantly different from ?one? and accordingly, do not represent constraint for the evolution of plasticity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.826

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 studies0.0000.002
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 head0.023
GPT teacher head0.247
Teacher spread0.224 · 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 designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

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