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Record W1949981539 · doi:10.1525/bio.2013.63.1.10

Regional Differences in Phosphorus Budgets in Intensive Soybean Agriculture

2013· article· en· W1949981539 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.

Bibliographic record

VenueBioScience · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsMcGill University
FundersGlobal Change Institute, University of the Witwatersrand, JohannesburgAndrew W. Mellon FoundationNational Science Foundation
KeywordsEutrophicationPhosphorusAgricultureFertilizerEnvironmental sciencePhosphorus deficiencyNutrientAgronomyAgricultural productivitySoil waterProduction (economics)Environmental protectionEcologyBiologyChemistrySoil scienceEconomics

Abstract

fetched live from OpenAlex

Fertilizer-intensive agriculture has been integral to increasing food production over the past half century but has been accompanied by environmental costs. We use case studies of phosphorus fertilizer use in the world's most productive soybean-growing regions, Iowa (United States), Mato Grosso (Brazil), and Buenos Aires (Argentina), to examine influences of management and soil type on agriculture's most prevalent phosphorus-related environmental consequences: eutrophication and consumption of Earth's finite phosphorus reserves. With increasing phosphorus inputs, achieving high yields on tropical soils with high phosphorus-binding capacity is becoming more common. This system has low eutrophication risks but increases demands on phosphorus supplies. In contrast, production in traditional breadbaskets, on soils with lower phosphorus-binding capacities, is being sustained with decreasing phosphorus inputs. However, in these regions, historical overuse of phosphorus may mean continued eutrophication risk even as pressures on phosphorus reserves diminish. We focus here on soybean production but illustrate how achieving sustainable agriculture involves an intricate optimization of local, regional, and global considerations.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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