Bibliographic record
Abstract
Each customs administration have to establish a partnership with the private sector in order to ensure the safety and security of the international trade supply chain. So, WCO developed a regime that will enhance the security and facilitation of international trade. This is the WCO Framework of Standards to Secure and Facilitation Global Trade. And developed countries devised and implemented Customs-Trade Partnership program, i.e. C-TPAT in U.S., PIP in Canada, StairSec in Sweden. The Customs-Trade Partnership programs in developed countries and WCO framework give some hints trade community in Korea which have not such a program. It is as follows. Firstly, it is necessary that the Customs-Trade Partnership program are developed and implemented in Korea. That program have to be included a validation process for Authorized Economic Operator. And it is necessary to offer incentives to AEO for voluntary cooperation to ensure the security of the international trade supply chain. Secondly, Korea Customs Service and Korea International Trade Association have to consider countermeasures against C-TPAT internationalization. That Customs-Trade Partnership program have to contribute an effective allocation of Customs resources, reduction of compliance cost, and strengthening of competitiveness of Trade community in Korea.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".