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Record W2133034177 · doi:10.1139/cjb-2014-0045

Effects of belowground herbivory on the survival and biomass of <i>Lolium perenne</i> and <i>Plantago lanceolata</i> plants at various growth stages

2014· article· en· W2133034177 on OpenAlexvenueno aff
Tomonori Tsunoda, Naoki Kachi, Jun‐Ichirou Suzuki

Bibliographic record

VenueBotany · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsnot available
FundersTokyo Metropolitan University
KeywordsLolium perenneBiologyPlantagoHerbivoreBotanyBiomass (ecology)Perennial plantPlantaginaceaeAgronomy

Abstract

fetched live from OpenAlex

We examined the effects of a root-feeding beetle larva (Anomala cuprea Hope) on the survival and biomass of Lolium perenne L. and Plantago lanceolata L. plants at various ages. We hypothesized that belowground herbivory would kill more juveniles than mature plants because of greater root damage. We predicted that for juvenile plants, mortality would be higher for P. lanceolata than for L. perenne, because the thin taproot of P. lanceolata is less tolerant to herbivory. We hypothesized that for mature plants, herbivory of fibrous roots would negatively affect biomass; thus, L. perenne would be less tolerant than P. lanceolata. Plants of L. perenne or P. lanceolata at four ages were grown in pots with or without a herbivore. Herbivores killed juvenile plants, but not mature plants, of both species. More juveniles of P. lanceolata than L. perenne were killed by herbivory. In P. lanceolata, the low biomass of juveniles was attributed to herbivory, but herbivory did not affect the biomass of mature plants. In contrast, herbivory negatively affected the biomass of L. perenne plants of all ages. We concluded that the effects of belowground herbivory depend on plant age and, thus, on plant growth stage and root architecture.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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