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Record W4296311674 · doi:10.1016/j.isci.2022.105048

A new dietary guideline balancing sustainability and nutrition for China’s rural and urban residents

2022· article· en· W4296311674 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

VenueiScience · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsMcGill University
FundersNatural Science Foundation of Anhui ProvinceNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsUrbanizationSustainabilityEutrophicationChinaLife-cycle assessmentSocioeconomic statusEnvironmental qualityGreenhouse gasEnvironmental healthEnvironmental scienceEnvironmental protectionGeographyAgricultural economicsNatural resource economicsNutrientProduction (economics)BiologyEcologyMedicineEconomicsPopulation

Abstract

fetched live from OpenAlex

Diets have important but often complex implications for both environmental quality and nutrition. We establish a production-oriented life cycle model to quantify and compare the farm-to-gate environmental impacts and food nutritional qualities underlying rural and urban diets in China from 1980 to 2019, a period of rapid urbanization and socioeconomic changes. The environmental impacts of rural diets were generally higher than those of urban diets, but this gap reduced after 2000. Environmental and nutritional values varied considerably across the 31 Chinese provinces due to their different food intakes and dietary structures. Dietary changes coinciding with urbanization increased greenhouse gas emissions, eutrophication potential, and nutritional quality, but decreased energy consumption and acidification potential. Based on our results, we propose a new dietary guideline to mitigate environmental impacts and improve nutritional quality.

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)0.001
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 score0.229
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.005
GPT teacher head0.238
Teacher spread0.233 · 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