PERSPECTIVES OF WHEAT AND BARLEY IMPORTERS ON LOGISTICS AND QUALITY
Bibliographic record
Abstract
This paper describes how the grain supply chains have been repeatedly studies from the shippers perspective, but the scope of such efforts usually end at the port of export. Consequently, end-users views of the supply chain are subject to scant analysis. This is a reflection of the emphasis that has been placed on the problems related to farmers, but it is also a function of the difficulty in under-taking meaningful research of global markets. This paper reports the results of a survey that was undertaken to assess the end-users' perspectives of the wheat and barley supply chains. The initial purpose was to identify buyers who would be willing to participate in trail shipments of grain in ISO containers. A global survey was undertaken to identify potential collaborators and to explore the logistical problems of end-users. Although agreement in principle to conduct trail shipments in containers were reached with several importers, delays and lack of cooperation on the part of the Canadian industry precluded this phase of the research. Nevertheless, the survey yielded interesting insights on the grain supply chain that suggests the export of grain in container load quantities could have great appeal to some end-users.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".