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Record W4413612643 · doi:10.3389/fmicb.2025.1662592

Rhizobia and non-rhizobial nodule bacteria with ACC deaminase increase both nodulation and stress resistance

2025· review· en· W4413612643 on OpenAlexaff
Elisa Gamalero, Bernard R. Glick

Bibliographic record

VenueFrontiers in Microbiology · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRhizobiaBacteriaRhizobiumBiologyMicrobiologySymbiosisNitrogenaseNitrogen fixationBradyrhizobiumRhizobiaceaeGenetics

Abstract

fetched live from OpenAlex

that possess the enzyme 1-aminocyclopropane-1-carboxylate (ACC) deaminase facilitate the nodulation of cognate legume hosts. Some rhizobial strains that contain ACC deaminase also help plants to overcome some types of environmental stress including heat, salt, drought and the presence of heavy metals. In addition, non-rhizobial strains of bacteria isolated from legume nodules that contain ACC deaminase increase the extent of rhizobia nodulation and the resistance of the legume to environmental stresses. Here, the literature addressing the role of ACC deaminase in increasing legume nodulation and protecting plants against a range of environmental stresses is summarized and discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.212
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

Explore more

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