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Record W2768090297 · doi:10.3389/fmicb.2017.02207

Trade, Diplomacy, and Warfare: The Quest for Elite Rhizobia Inoculant Strains

2017· article· en· W2768090297 on OpenAlexfundno aff
Alice Checcucci, George C. diCenzo, Marco Bazzicalupo, Alessio Mengoni

Bibliographic record

VenueFrontiers in Microbiology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversità degli Studi di Firenze
KeywordsRhizobiaMicrobial inoculantBiologyNitrogen fixationSymbiosisPopulationAgricultureEcologyInoculationBacteria

Abstract

fetched live from OpenAlex

Rhizobia form symbiotic nitrogen-fixing nodules on leguminous plants, which provides an important source of fixed nitrogen input into the soil ecosystem. The improvement of symbiotic nitrogen fixation is one of the main challenges facing agriculture research. Doing so will reduce the usage of chemical nitrogen fertilizer, contributing to the development of sustainable agriculture practices to deal with the increasing global human population. Sociomicrobiological studies of rhizobia have become a model for the study of the evolution of mutualistic interactions. The exploitation of the wide range of social interactions rhizobia establish among themselves, with the soil and root microbiota, and with the host plant, could constitute a great advantage in the development of a new generation of highly effective rhizobia inoculants. Here, we provide a brief overview of the current knowledge on three main aspects of rhizobia interaction: trade of fixed nitrogen with the plant; diplomacy in terms of communication and possible synergistic effects; and warfare, as antagonism and plant control over symbiosis. Then, we propose new areas of investigation and the selection of strains based on the combination of the genetic determinants for the relevant rhizobia symbiotic behavioral phenotypes.

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 score0.847
Threshold uncertainty score0.384

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 science0.0010.000
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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

Citations103
Published2017
Admission routes1
Has abstractyes

Explore more

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