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Record W4289884526 · doi:10.1002/crso.20218

Gulf of Mexico Hypoxia 2022: What’s the Role of Plant Nutrition?

2022· article· en· W4289884526 on OpenAlexaff
Tom Bruulsema

Bibliographic record

VenueCrops & Soils · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsPlant Biotechnology Institute
Fundersnot available
KeywordsAgricultureHypoxia (environmental)WatershedEnvironmental scienceNutrient managementNutrientAgricultural scienceWater resource managementAgricultural engineeringBiologyEcologyEngineeringComputer scienceChemistry

Abstract

fetched live from OpenAlex

Hypoxia in the Gulf of Mexico is an environmental issue connected to agricultural crop management in the Mississippi River watershed. Programs to improve nutrient stewardship in this watershed aim to improve nutrient use efficiency and reduce losses of nitrogen and phosphorus. Trends since the 1980s show increases in both crop production and the size of the hypoxic zone while the trends in nitrogen surplus have neither increased nor decreased. Provisional flow‐normalized river loads of nitrogen are decreasing. While improvements in adoption of 4R management of applied fertilizers and manures have been noted, opportunities for improvement also remain. While 4R practices will not solve the issue on their own, they can make an important contribution when integrated with soil conservation practices and changes to whole farming systems. Earn 1 CEU in Nutrient Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses .

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.006
GPT teacher head0.192
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

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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2022
Admission routes1
Has abstractyes

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