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Definition of sustainable and unsustainable issues in nutrient management of modern agriculture

2005· article· en· W2166778880 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

VenueSoil Use and Management · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsNutrient managementNutrientAgricultureEnvironmental scienceNutrient cycleBusinessNutrient pollutionSustainable agricultureProduction (economics)Natural resource economicsAgricultural engineeringEcologyEngineeringEconomicsBiology

Abstract

fetched live from OpenAlex

Abstract. Sustainable management of nutrients in agricultural systems is critical for sufficient production of nutritious foods and to minimize environmental pollution. In this overview, we discuss some of the most important factors influencing nutrient cycling, and how practices for sustainable nutrient management can be optimized. In most cases, problems are associated with excessive use of nutrients (manures, other organic amendments, and inorganic fertilizers). Options for dealing with such problems at the farm level include: reducing nutrient inputs to balance exports, increasing the land area on which manures are applied, and export of excess nutrients from the farm in the form of value‐added products. These strategies can be used singly, or in combination. Nutrients in the human food chain are often not recycled back to primary crop production. To manage such issues, and avoid regional nutrient accumulations, we need to develop a better understanding of large‐scale nutrient flows, and develop policies to manage them. We stress the importance of scale when considering nutrient management in the future.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.195
Teacher spread0.187 · 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