A study on the AVI/AEI International standardization and development of the Korea standard
Bibliographic record
Abstract
This International Standard establishes an AVI/AEI System based on radio frequency technologies. This system is intended for general application in ITS. Specially, It allows the transfer of the identification codes and further information about equipment and vehicles used in intermodal transport into such CVO and information systems related to Intermodal Transport processes. The aim of this standard is to define, describe and specify Architecture, System Parameters, Numbering/ Data structures and interface related to an AVI/AEI system to provide an enabling Standard, which, whilst allowing the system specifier to determine the performance levels and operating conditions, provides a framework for nominal interoperability. The Standard is to establish a common framework to achieve unambiguous identification in AVI/AEI applications. Thes is AVI/AEI is designed to be an 'enabling' structure to allow interoperability between different commercial systems, and not prescriptive in determining any one system. The ISO TC204 WG4 has eight active work items. A new WI on ERI is progressing quickly; three WIs for the road environment and four multimodal WIs are under development. All Work Items are joint between CEN TC278 and ISO TC204 according to the Vienna Agreement, with CEN in the lead. The work is progressing with some delay. For all the work items, the countries who have appointed experts we: Australia, Austria, Belgium, Canada, Czech, Denmark France, Germany, Japan, Korea, the Netherlands, Norway, Spain, Sweden, UK and USA. There are 30 registered experts. The study focus on the AVI/AEcl standardization and developing of the Korea standard
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".