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Record W4391684207 · doi:10.3390/crops4010004

Root Exudate Metabolites Alter Food Crops Microbiomes, Impacting Plant Biocontrol and Growth

2024· article· en· W4391684207 on OpenAlexaff
Shimaila Ali, Bernard R. Glick

Bibliographic record

VenueCrops · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsUniversity of WaterlooAgriculture and Agri-Food Canada
Fundersnot available
KeywordsExudateMicrobiomeBiologyBiological pest controlPlant growthRhizosphereBotanyBiotechnologyAgronomyBacteria

Abstract

fetched live from OpenAlex

Exuded plant metabolites play an important role in fostering beneficial interactions with the surrounding soil microbiota, thereby helping plants to better adjust to changing environmental conditions. These metabolites act as signals to attract or enhance the colonization of plant roots with specific groups of beneficial microbes and they modulate the dynamics of plant–microbe interactions in fulfilling plant niche-based requirements, directly and/or indirectly. This review emphasizes the expression, levels, modes of action, and net effects of the signaling metabolites that help food crop plants to become colonized by microbes that promote plant growth and development under periods of biotic stress.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.350

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 head0.206
Teacher spread0.197 · 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 designBench or experimental
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

Citations22
Published2024
Admission routes1
Has abstractyes

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