Sustainability of agricultural trade supply chains status, opportunities, and future directions
Bibliographic record
Abstract
This study examines the sustainability of Agricultural Trade Supply Chains (ATSC) from the perspective of agricultural sustainable development, with a focus on five key aspects: production, processing and storage, transportation and logistics, trade, and consumer and market. Based on an analysis of 756 academic papers published between 2013 and 2022, scientific metric techniques were used to identify changes in the field's sustainability. The study highlights opportunities for the development of a sustainable agricultural product trade supply chain, including the use of blockchain technology to improve transparency and traceability, increasing consumer demand for sustainable and eco-friendly products, corporate zero-deforestation commitments, bioenergy market expansion, and the role of farm advisors in promoting sustainable production methods. This paper contributes to a structured understanding of the status and future directions of ATSC sustainability, emphasizing the importance of joint efforts across all links of the supply chain to meet the sustainable needs of consumers and promote environmental protection and social-friendly markets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".