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Record W4399683047 · doi:10.3934/microbiol.2024021

Use of plant growth-promoting bacteria to facilitate phytoremediation

2024· review· en· W4399683047 on OpenAlexaff
Elisa Gamalero, Bernard R. Glick

Bibliographic record

VenueAIMS Microbiology · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhytoremediationPlant growthBacteriaEnvironmental scienceBiotechnologyBiologyAgronomyEcologyContamination

Abstract

fetched live from OpenAlex

Here, phytoremediation studies of toxic metal and organic compounds using plants augmented with plant growth-promoting bacteria, published in the past few years, were summarized and reviewed. These studies complemented and extended the many earlier studies in this area of research. The studies summarized here employed a wide range of non-agricultural plants including various grasses indigenous to regions of the world. The plant growth-promoting bacteria used a range of different known mechanisms to promote plant growth in the presence of metallic and/or organic toxicants and thereby improve the phytoremediation ability of most plants. Both rhizosphere and endophyte PGPB strains have been found to be effective within various phytoremediation schemes. Consortia consisting of several PGPB were often more effective than individual PGPB in assisting phytoremediation in the presence of metallic and/or organic environmental contaminants.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.087
GPT teacher head0.256
Teacher spread0.168 · 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 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

Citations23
Published2024
Admission routes1
Has abstractyes

Explore more

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