European pork chains : diversity and quality challenges in consumer-oriented production and distribution
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.
Bibliographic record
Abstract
In this book the results are presented of a comprehensive inventory of pork chains that has been conducted through expert interviews and in-depth case studies. The main focus of the book is on how well diverse and fragmented supply in the European pork sector matches differentiating demands for pork products in rapidly evolving markets. One of the central topics discussed in the book is management of quality in diverse mainstream and specialty European pork chains. Inter-enterprise information systems, governance forms, logistics and sustainability aspects of European pork chains are also presented, as well as a number of interesting innovations in the chains. 'European pork chains' consists of four chapters that discuss the European pork chain as a whole and nine chapters that present case studies. The latter comprise three specialty pork chains (Iberian ham from Spain, Mangalica pork from Hungary, and organic pork from the Netherlands) and three regional pork chains in Europe (a Greek integrated chain, the German 'Eichenhof' chain and the French 'Cochon de Bretagne' chain). To enable comparison with chains outside Europe, a review of pork chains in China, Canada, Brazil and South Africa has been included.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it