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Record W2047940210 · doi:10.1139/b07-139

Leaf variegation is associated with reduced herbivore damage in <i>Hydrophyllum virginianum</i>

2008· article· en· W2047940210 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueBotany · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsVariegation (histology)HerbivoreBiologyBotanyPhotosynthesis

Abstract

fetched live from OpenAlex

Leaf variegation refers to local regions of the upper surface of a leaf having reduced or obstructed chlorophyll, which results in whitish spots. These lighter spots may compromise the photosynthetic efficiency of a leaf, and many competing hypotheses have been put forward to explain why this patterning may be adaptive. It has been suggested that variegation is either an adaptive response to environmental conditions or a defence mechanism against herbivore damage. To test whether leaf variegation reduces herbivore damage, we first assessed the frequency of variegated and nonvariegated leaves in natural populations of the plant Hydrophyllum virginianum L., and second, measured herbivore damage to both variegated and nonvariegated leaves. We found that variegated leaves were present at high frequencies within natural populations (6%–31%) and that nonvariegated leaves sustained nearly twice the amount of damage by comparison with variegated leaves. Therefore, leaf variegation appears to be beneficial by reducing herbivore damage to leaves. These data are consistent with the fundamental prediction of the herbivory hypothesis for the benefits of leaf variegation.

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.

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 score0.856
Threshold uncertainty score0.305

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 head0.030
GPT teacher head0.193
Teacher spread0.163 · 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