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Record W3158508141 · doi:10.1093/jxb/erab198

Split-root assays for studying legume–rhizobia symbioses, rhizodeposition, and belowground nitrogen transfer in legumes

2021· review· en· W3158508141 on OpenAlexafffund
Malinda S. Thilakarathna, Kevin R. Cope

Bibliographic record

VenueJournal of Experimental Botany · 2021
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRhizobiaLegumeSymbiosisNitrogen fixationAgronomyBiologyRoot noduleNitrogenFabaceaeRhizobiumBotanyChemistryBacteriaHorticultureInoculation

Abstract

fetched live from OpenAlex

Split-root assays have been used widely in studies focused on understanding the complex regulatory mechanisms in legume-rhizobia symbioses, root nitrogen rhizodeposition, and belowground nitrogen transfer, and the effects of different biotic/abiotic factors on this symbiotic interaction. This assay allows a plant to have a root system that is physically divided into two distinct sections that are both still attached to a common shoot. Thus, each root section can be treated separately to monitor local and systemic plant responses. Different techniques are used to establish split-root assemblies, including double-pot systems, divided growth pouches, elbow root assembly, twin-tube systems, a single pot or chamber with a partition in the center, and divided agar plates. This review is focused on discussing the various types of split-root assays currently used in legume-based studies, and their associated advantages and limitations. Furthermore, this review also focuses on how split-root assays have been used for studies on nitrogen rhizodeposition, belowground nitrogen transfer, systemic regulation of nodulation, and biotic and abiotic factors affecting legume-rhizobia symbioses.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.739
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.298
Teacher spread0.256 · 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.

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

Citations17
Published2021
Admission routes2
Has abstractyes

Explore more

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