Bibliographic record
Abstract
The central issue addressed in this paper is the attributes preferred by a sample of buyers of durum wheat grown in Canada. Primary emphasis is the value placed on certain visual and nonvisual attributes by US buyers of durum wheat. In addition, a source variable in the analysis is used to test preferences of US buyers for US-source compared to Canadian-source durum. The latter is a method to test whether durum millers in the US believe that Canadian durum is a superior product, a view widely-held in the Canadian grain trade. Results indicate that higher bushel weight has a positive effect on purchase probability, and appears to be more important to buyers’ purchasing decision than protein content, amylase content, or the choice between no. 1 and no. 2 grade. US millers in the study are shown either a) to prefer US-grown durum over that from Canada, or b) to dislike the single desk seller arrangements involved in purchasing Canadian durum. It appears that US managers who grow or market durum wheat have a competitive edge over their Canadian competitors when marketing to US-based durum users.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".