Bibliographic record
Abstract
Agricultural and Livestock product of Chungbuk export 97 countries by 2008 year. Percentage of high ranking 10 country among their countries is 75.3% Asia, the north America, Oceania region is the most exported region, The main import countries is India, Sri Lanka, Singapore, Vietnam, Hongkong, Japan, Nigeria, Latvia, Canada, Belgium. Export Item of agricultural and Livestock product is 26 items by HSK unit. Among fresh agricultural and livestock product, the most hopeful export item is order of fruits, vegetables, fungi. The most exported product in chugbuk is delicatessen, vegetable matter juice, vegetableㆍfruit or nuts. This item is similar in item to export item of our country. The main competition country is China, Japan, the USA, and our competition rival country is China in the USA and Japan, Japan in China, China and the USA in Southeast Asia, Japan in Taiwan, Russia, and Hongkong. Competition power of their countries is basis of cheaply prices in china, high quality in Japan, high quality contradistinction prices in the USA. Therefore, for continuous export increase, there need building the differentiation of our product. For export increase of agricultural and livestock, agro-food, there must prepared entry strategy based on export possibility by item, survey on market condition by country. The export is able to fulfill all condition point of the viewpoint of product, distribution, and marketing. Therefore it needs policy support on sector to low efficiency, or in difficult circumstances carrying out each export firm. Thus, to increase export agricultural and livestock product of Chungcheongbuk-do, need an overseas information activity and raise brand awareness of chungbuk, stable supply and prepare quality administration basis, promote export organization, and improve distribution condition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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".