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Plant- and microbial-based mechanisms to improve the agronomic effectiveness of phosphate rock: a review

2006· review· en· W1999543783 on OpenAlexafffundabout
Melissa Arcand, Kim Schneider

Bibliographic record

VenueAnais da Academia Brasileira de Ciências · 2006
Typereview
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhosphoritePhosphorusEnvironmental sciencePhosphateLimitingAgricultureCrop productionAgronomyChemistryEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Deficiency in plant-available phosphorus is considered to be a major limiting factor to food production in many agricultural soils. Mineral resources are necessary to restore soil phosphorus content. In regions where conventional fertilizers are not used due to cost limitations or to mitigate adverse environmental effects, local sources of phosphate rock are being increasingly recognized for potential use as alternative phosphorus fertilizers. The main obstacle associated with using directly applied ground phosphate rock is that the phosphate released is often unable to supply sufficient plant-available phosphorus for crop uptake. Plantand microbial-based mechanisms are low-cost, appropriate technologies to enhance the solubilization and increase the agronomic effectiveness of phosphate rock. Common mechanisms of phosphate rock dissolution including proton and organic acid production will be reviewed for both plants and microorganisms. This review will also address possibilities for future research directions and applications to agriculture, as well as highlight ongoing research at the University of Guelph, Guelph, Canada.

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)0.001
metaresearch head score (Gemma)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.017
GPT teacher head0.270
Teacher spread0.252 · 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

Citations217
Published2006
Admission routes3
Has abstractyes

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