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Record W2531268193 · doi:10.2134/ael2016.07.0024

Distant Views and Local Realities: The Limits of Global Assessments to Restore the Fragmented Phosphorus Cycle

2016· article· en· W2531268193 on OpenAlex
Andrew N. Sharpley, Peter J. A. Kleinman, Helen P. Jarvie, Don Flaten

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

VenueAgricultural & Environmental Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAgricultureBig dataProduction (economics)Agricultural productivityBusinessResource (disambiguation)Environmental resource managementNatural resource economicsComputer scienceEconomicsGeography

Abstract

fetched live from OpenAlex

Core Ideas Meta‐analysis of “big data” can identify P disconnects in P cycles, stocks and flows. Understanding of farming realities is needed to identify root causes of change. Access to “big data” without grounding in reality can lead to misleading conclusions. Researchers must ensure production and conservation tactics consider farming realities. With more sophisticated data compilation and analytical capabilities, the evolution of “big data” analysis has occurred rapidly. We examine the meta‐analysis of “big data” representing phosphorus (P) flows and stocks in global agriculture and address the need to consider local nuances of farm operations to avoid erroneous or misleading recommendations. Of concern is the disconnect between macro‐needs for better P resource management at regional and national scales versus local realities of P management at farm scales. Both agricultural and environmental researchers should focus on providing solutions to disconnects identified by meta‐analyses and ensure that production and conservation strategies consider farming realities.

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 score0.073
Threshold uncertainty score0.340

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 studies0.0000.001
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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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