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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 OpenAlex

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 · 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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
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