Bibliographic record
Abstract
Since the terrorist attacks on September 11, 2001 in U.S.A., a number of initiatives that have the aim of strengthening security in the international supply chain have been made. Customs-Business Partnership programs among such initiatives are being introduced, developed and implemented in developed countries in order to ensure the security of the international trade supply chain and to overcome limitation of control goods moving across the border in customs adminstration. Customs-Business Partnership programs include US C-TPAT, Canada's Partners in Protection(PIP), EU's AEO, and Sweden's StairSec Programme. Korean Customs Services has introduces AEO program in the end of 2007. EU and Australia conducted AEO Pilot project before implementation of AEO program. There are effective methods to operate Authorized Economic Operators System in Korea through lessons learned by AEO Pilot projects in EU and Australia, as follows. ① Pilot project should be conducted before implementation of AEO program. ② AEO guideline for each economic operators should be drawn up. ③ AEO programs is operated not compulsively but voluntarily. ④ All security certificates already issued should be taken into account. ⑤ A client coordinator or contact point in Customs should be appointed for effective communication with AEO. ⑥ AEOs could require security declaration to their partners in order to have an end-to-end supply chain security. ⑦ Customs could demonstrate collateral or direct benefits to AEOs who have made supply chain security investments. ⑧ AEO program should be driven to achieve mutual recognition which recognize AEO status in another country.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.065 | 0.021 |
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".