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Ontogenetic switches from plant resistance to tolerance: minimizing costs with age?

2007· article· en· W2150830818 on OpenAlexaff
Karina Boege, Rodolfo Dirzo, David H. Siemens, P. D. Brown

Bibliographic record

VenueEcology Letters · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsTrinity Western UniversityWestern University
FundersNational Center for Research Resources
KeywordsOntogenyBiologyResistance (ecology)HerbivoreEcologyJuvenileResource (disambiguation)Vulnerability (computing)Computer science

Abstract

fetched live from OpenAlex

Changes in herbivory and resource availability during a plant's development should promote ontogenetic shifts in resistance and tolerance, if the costs and benefits of these basic strategies also change as plants develop. We proposed and tested a general model to detect the expression of ontogenetic tradeoffs for these two alternative anti-herbivory strategies in Raphanus sativus. We found that ontogenetic trajectories occur in both resistance and tolerance but in opposite directions. The juvenile stage was more resistant but less tolerant than the reproductive stage. The ontogenetic switch from resistance to tolerance was consistent with the greater vulnerability of young plants to leaf damage and with the costs of resistance and tolerance found at each stage. We posit that the ontogenetic perspective presented here will be helpful in resolving the current debate on the existence and detection of a general resistance-tolerance tradeoff.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.191
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), 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

Citations131
Published2007
Admission routes1
Has abstractyes

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