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Record W2000671311 · doi:10.1094/pdis-06-10-0446

Exogenous Applications of Abscisic Acid Increase Curing of Pierce's Disease-Affected Grapevines Growing in Pots

2010· article· en· W2000671311 on OpenAlexfundno aff
Melody M. Meyer, Bruce C. Kirkpatrick

Bibliographic record

VenuePlant Disease · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytoplasmas and Hemiptera pathogens
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsAbscisic acidBiologyXylemXylella fastidiosaVitis viniferaHorticultureCuring (chemistry)BotanyBacteriaChemistry

Abstract

fetched live from OpenAlex

Foliar and drench applications of the plant growth regulator abscisic acid (ABA) were applied to 1-year-old potted Vitis vinifera 'Pinot Noir' and 'Cabernet Sauvignon' vines infected with Xylella fastidiosa, the bacterial pathogen that causes Pierce's disease (PD). A naturally occurring ABA and a synthetic ABA were applied, and both materials showed some effectiveness at increasing curing rates of PD-affected grapevines. Pinot Noir grapevines treated with the drench ABA treatments had significantly greater disease curing effects than the unsprayed control plants. It has been shown that plant phenolics have antimicrobial properties, and we found a positive correlation between effective ABA treatments and the total phenolic compound content of xylem sap extracted from Pinot Noir vines.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.245

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 head0.010
GPT teacher head0.201
Teacher spread0.191 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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