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Record W4200443088 · doi:10.1002/crso.20165

Nutrient Stewardship: Taking 4R Further

2021· article· en· W4200443088 on OpenAlexaff
Tom Bruulsema

Bibliographic record

VenueCrops & Soils · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsPlant Biotechnology Institute
Fundersnot available
KeywordsStewardship (theology)Process (computing)Reading (process)Environmental stewardshipNutrientComputer scienceAgricultural engineeringEngineering managementBusinessPolitical scienceEnvironmental resource managementEnvironmental scienceEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

Abstract It’s been 10 years since the 4R Plant Nutrition manual was published, setting out principles for the stewardship of plant nutrients agreed to by soil fertility scientists and crop nutrition practitioners. Since then, the industry has done a lot to implement the concept, both globally and in North America. What has been learned and accomplished in the process? What needs to be done to take 4R further? Earn 1 CEU in Nutrient Management by reading this article and taking the quiz at https://bit.ly/3potolp . View all CEUs online 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)0.034
metaresearch head score (Gemma)0.041
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.068
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0110.015
Open science0.0030.014
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0680.027

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 head0.020
GPT teacher head0.234
Teacher spread0.214 · 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
GenreCommentary

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

Citations7
Published2021
Admission routes1
Has abstractyes

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