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Assessment on Ecological Safety of Farmland Fertilization of China

2014· article· en· W2065427772 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

VenueAdvanced materials research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Quality and Pollution
Canadian institutionsUniversity of Saskatchewan
FundersNanjing UniversityState Administration of Foreign Experts AffairsChinese Academy of SciencesCanada Research ChairsState Key Laboratory in Marine Pollution
KeywordsChinaHuman fertilizationAgricultureHazardEnvironmental scienceEcologyGeographyEnvironmental protectionAgronomyBiology

Abstract

fetched live from OpenAlex

Here is presented the concepts of Fertilization Ecological Hazard Index (FEHI) and Fertilization Ecological Safety Threshold (FEST). These concepts have been used to develop models that assess the hazards posed by fertilization with inorganic fertilizers on ecological environments in China. Based on these models, there were 11 regions, most of which are located in Western China, slightly at risk from over-fertilization, while 14 regions located in central or eastern China were at a moderate hazard from overuse of fertilizers. Six regions in western China were found at ecological safety of environment because of small amounts of fertilizers used in these regions. Ecological safety of environment decreased along the gradient from northwest to southeast by fertilization. There were several factors that influence FEHI. It is obligatory for local governments to offer training to guide reasonable uses of fertilization. It would be prudent for China to establish laws to protect soils, especially to regulate the use of fertilizers in agriculture.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0040.000

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 head0.373
Teacher spread0.339 · 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