Gestión de seguridad integral en el transporte de carga para la distribución física internacional
Bibliographic record
Abstract
The article presents the Comprehensive Security Management in the transportation of cargo for the international physical distribution of the company Transcastillo S.A., considering the security of the attached operations, crimes, robberies or terrorist acts, in the company there have been no terrorist acts, but the drivers have been victims of robberies, road safety all have a type E license, active security at this point the company requires that the vehicles are in constant preventive maintenance, passive security have a seat belt, however they do not have an airbag, carrying out the analysis of the cargo to be transported, most of which are products of easy reduction, the mode of transport, the costs were analyzed, the terms of negotiation, the enabling documents and the transport operations, based on the methodology analyzed in the ECLAC. Transcastillo S.A.'s comprehensive security management system has some shortcomings, such as the lack of a comprehensive security management guide that also considers active and passive security. It also has strong points, such as satellite tracking for all units involved in international physical distribution operations. Finally, international physical distribution transactions averaged 12% from the second quarter of 2021 to the third quarter of 2024: exports 12%, imports 11%, and EU customs transits 77%, with the majority of transactions and effective orders delivered originating in Tumbes and destined for Ipiales.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".