MétaCan
Menu
Back to cohort
Record W2060647962 · doi:10.1371/journal.pbio.1001124

Fertilizing Nature: A Tragedy of Excess in the Commons

2011· article· en· W2060647962 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePLoS Biology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Alberta
FundersAlberta Crop Industry Development Fund
KeywordsNutrient pollutionAgricultureBiologyNutrientFertilizerNatural resource economicsTragedy of the commonsGlobal warmingEnvironmental scienceClimate changeAquatic ecosystemEnvironmental protectionEcologyAgronomyCommons

Abstract

fetched live from OpenAlex

Globally, we are applying excessive nitrogen (N) fertilizers to our agricultural crops, which ultimately causes nitrogen pollution to our ecosphere. The atmosphere is polluted by N₂O and NO(x) gases that directly and indirectly increase atmospheric warming and climate change. Nitrogen is also leached from agricultural lands as the water-soluble form NO₃⁻, which increases nutrient overload in rivers, lakes, and oceans, causing "dead zones", reducing property values and the diversity of aquatic life, and damaging our drinking water and aquatic-associated industries such as fishing and tourism. Why do some countries show reductions in fertilizer use while others show increasing use? What N fertilizer application reductions could occur, without compromising crop yields? And what are the economic and environmental benefits of using directed nutrient management strategies?

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 score0.043
Threshold uncertainty score0.121

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 head0.035
GPT teacher head0.234
Teacher spread0.199 · 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