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Record W4391717124 · doi:10.1002/jeq2.20546

The importance of consensus science to managing phosphorus in the environment: SERA‐17 and the legacy of Andrew Sharpley

2024· article· en· W4391717124 on OpenAlexaff
Merrin L. Macrae, Peter J. A. Kleinman, Deanna L. Osmond, Amy L. Shober, Nathan O. Nelson

Bibliographic record

VenueJournal of Environmental Quality · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsConsistency (knowledge bases)AgricultureDiversity (politics)Process (computing)PhosphorusKnowledge managementPolitical scienceEngineering ethicsSociologyProcess managementComputer scienceBusinessEngineeringEcologyChemistryBiology

Abstract

fetched live from OpenAlex

Phosphorus (P) loss from agricultural systems to surface waters, and ultimately, eutrophication, presents a wicked problem requiring transdisciplinary solutions. The mission of SERA-17 (Southern Extension and Research Advisory Information Exchange Group-17) has been to address this problem by developing "Innovative Solutions to Minimize Phosphorus Losses from Agriculture." Over the course of his career, Dr. Andrew Sharpley demonstrated a rare ability to collaboratively achieve consensus around issues related to the science and management of P. The SERA-17 organization served as the central community of experts and stakeholders where that consensus was built and applied. The consensus-based approach, demonstrated by Sharpley and at the core of the SERA-17 organization, was routinely applied to key areas of P science to produce applied outcomes that have been readily adopted: advance foundational science to resolve knowledge gaps and to promote innovation; promote consistency in methods to facilitate comprehensive investigations and conclusions across a diversity of systems; engage diverse stakeholders to prioritize research, and ultimately, ensure that outcomes reflect a plurality of perspectives; and deliver pragmatic solutions that reflect the best information available at a particular time. We review the history of SERA-17 in delivering new science and management recommendations for P, with an eye to elucidating Sharpley's role and legacy in this process.

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 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)0.005
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 score0.020
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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 teacher head, 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

Citations8
Published2024
Admission routes1
Has abstractyes

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