Sustainability of the Air Cargo Handling Process in the Context of Safety and Environmental Aspects
Bibliographic record
Abstract
In addition to passenger traffic, air cargo business is an important business for a global air transport industry. This means that Air Cargo Handling Process (ACHP) is important for any airport or cargo handling agent who provides cargo handling services. To qualitatively manage the ACHP, certain prerequisites must be met, such as competent cargo staff, procedures, cargo information system, infrastructure with enough capacity, and process management. The objective of research presented in this paper is ACHP and its complex structure but in the context of safety and sustainability. Using of several scientific methods of cognition, the authors research the structure of ACHP and safety, and ecological aspects of the process, too. The result of this research is the safety and environmental aspects of the process which are of significant importance for process functionality as well as for the quality level of service that meets customer requirements and to the sustainability of process. Results show that there is a significant impact of the environmental and safety aspects specific to particular activities in ACHP and that they affect the reliability and functionality of the whole process, its profitability, and competitiveness. This points to the need for ACHP to be viewed in context and to understand ACHP sustainability matters and sustainability components.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".