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Record W4316040572 · doi:10.3389/fpls.2022.1085998

Aluminum in plant: Benefits, toxicity and tolerance mechanisms

2023· review· en· W4316040572 on OpenAlexafffund
Raphael Ofoe, Raymond Thomas, Samuel K. Asiedu, Gefu Wang‐Pruski, Bourlaye Fofana, Lord Abbey

Bibliographic record

VenueFrontiers in Plant Science · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAluminum toxicity and tolerance in plants and animals
Canadian institutionsAgriculture and Agri-Food CanadaMemorial University of NewfoundlandDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAbiotic componentPlant growthLimitingNutrientCrop productivitySoil waterBiologyDetoxification (alternative medicine)ToxicityCropAgronomyPhytotoxicityProductivityEnvironmental scienceChemistryEcology

Abstract

fetched live from OpenAlex

Aluminum (Al) is the third most ubiquitous metal in the earth's crust. A decrease in soil pH below 5 increases its solubility and availability. However, its impact on plants depends largely on concentration, exposure time, plant species, developmental age, and growing conditions. Although Al can be beneficial to plants by stimulating growth and mitigating biotic and abiotic stresses, it remains unknown how Al mediates these effects since its biological significance in cellular systems is still unidentified. Al is considered a major limiting factor restricting plant growth and productivity in acidic soils. It instigates a series of phytotoxic symptoms in several Al-sensitive crops with inhibition of root growth and restriction of water and nutrient uptake as the obvious symptoms. This review explores advances in Al benefits, toxicity and tolerance mechanisms employed by plants on acidic soils. These insights will provide directions and future prospects for potential crop improvement.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.047
GPT teacher head0.256
Teacher spread0.209 · 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

Citations248
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Plant ScienceSame topicAluminum toxicity and tolerance in plants and animalsFrench-language works237,207