Zdolność konkurencyjna przemysłu spożywczego krajów UE, USA i Kanady na rynku światowym
Bibliographic record
Abstract
The aim of the paper was to assess the competitive capacity of the main sectors of the EU, the US and Canadian food industry, using selected economic and trade indicators.Time range of the research covered the years 2007-2016.The research is based on the data from the Statistical Office of the European Union (Eurostat), the US Census Bureau, the USDA Foreign Agricultural Service's Global Agricultural Trade System (FAS/USDA) and Agriculture and Agri-food Canada.It was proved that improvement of the competitive position of the EU food industry was more determined by the scale of activity in world trade (increasing share in global exports), while competitive advantages of the US and Canadian food industry were influenced by economic advantages associated with improving the economic performance of enterprises in a given sector, its share in the real value added of the food industry as a whole and labour productivity.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.036 |
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; both teacher heads agree on what is shown here.
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".