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Record W2101475982 · doi:10.2298/abs1404659m

Effects of pedunculate oak tree vitality on gypsy moth preference and performance

2014· article· en· W2101475982 on OpenAlexaff
Slobodan Milanović, Ljubodrag Mihajlović, Dragan Karadžić, L. Jankovský, P. Aleksić, Milena Janković‐Tomanić, Jelica Lazarević

Bibliographic record

VenueArchives of Biological Sciences · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsInstitute for Biological Sciences
FundersEuropean Social FundDirectorate for Biological SciencesMendelova Univerzita v BrněMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsGypsy mothBiologyVitalityPowdery mildewLarvaEcologyBotany

Abstract

fetched live from OpenAlex

Gypsy moths and powdery mildew play a significant role in oak decline processes. However, information is lacking on the effects on the gypsy moth of impaired tree vitality caused by defoliation or parasite infection. We assessed how pedunculate oak leaves collected from vigorous, declining, and infected trees influenced gypsy moth preference and performance (growth and nutritional indices). We found a negative effect of powdery mildew-infected leaves on gypsy moth performance, while declining trees had positive effects on gypsy moth performance and preference. All examined parameters of larvae fed declining oak leaves were higher than those of larvae fed vigorous oak leaves. Increased growth on declining oak leaves was caused by both higher consumption and more efficient food utilization. The results of this research could help us to better understand multitrophic interactions in complex communities such as oak forests.

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 score0.219
Threshold uncertainty score0.851

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 head0.018
GPT teacher head0.216
Teacher spread0.199 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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