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Record W4206524890 · doi:10.3389/fpls.2021.796045

The Rhizobium-Legume Symbiosis: Co-opting Successful Stress Management

2022· review· en· W4206524890 on OpenAlex
Justin P. Hawkins, Ivan J. Oresnik

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Plant Science · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRhizobiaRhizobiumSymbiosisBiologyLegumeBacteriaBotanyGenetics

Abstract

fetched live from OpenAlex

The interaction of bacteria with plants can result in either a positive, negative, or neutral association. The rhizobium-legume interaction is a well-studied model system of a process that is considered a positive interaction. This process has evolved to require a complex signal exchange between the host and the symbiont. During this process, rhizobia are subject to several stresses, including low pH, oxidative stress, osmotic stress, as well as growth inhibiting plant peptides. A great deal of work has been carried out to characterize the bacterial response to these stresses. Many of the responses to stress are also observed to have key roles in symbiotic signaling. We propose that stress tolerance responses have been co-opted by the plant and bacterial partners to play a role in the complex signal exchange that occurs between rhizobia and legumes to establish functional symbiosis. This review will cover how rhizobia tolerate stresses, and how aspects of these tolerance mechanisms play a role in signal exchange between rhizobia and legumes.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0040.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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