Bibliographic record
Abstract
A long history of producing mostly for the domestic market led to institutions and "ways of thinking" that left Canadian producers ill prepared for major exposure to the severe demands of the international market place. The industry expansion that started in earnest in the mid-1980s led by enthusiastic producers and supportive government policies developed into a situation where suppliers became vulnerable to the closure of export markets. Efforts by governments to negotiate international trade accords to prevent indiscriminate border closures ultimately proved fruitless in the face of the BSE discovery in Canada. Moreover, governments, primary producers and packers in Canada appeared to have learned little from the British experience of long term closures to export markets and were not well prepared for the eventuality of discovering BSE in Canada. For the long term success of the Canadian beef sector, it is important to continue to seek international agreement on appropriate protocols that not only limits consumer exposure to animal diseases and pests but also takes account of the real risk to human health as based on scientific knowledge and evidence. At the same time, Canadian beef producers need to be cognizant of their vulnerability to export markets and so adopt production practices and supply chains that are in line with changing consumer wants in export markets.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".