Bibliographic record
Abstract
Managing the north-south traffic stream through Switzerland is a major challenge at the beginning of the 21st century. Setting the goals to protect the Alps against the nuisances caused by traffic and to improve safety in the long tunnels, where security is a critical issue, has lead to the adoption of measures focusing on goods These measures apply first of all to the roads, and in particular to the St Gotthard and St Bernardino road tunnels through the Alps. Limiting the freight traffic going through the tunnels, in order to ensure users safety, was a result of a strategic decision. This strategy is supplemented by another policy that shifts freight transport from the road onto the railways. To achieve this, tremendous investments have been granted to make rail goods transport across the Alps more competitive, leading to the construction of two very important railway tunnels. The report describes the four main Swiss roads crossing the Alps and the number of heavy goods vehicles using these routes in 2005 and the first quarter of 2006. Following the fire in the St Gotthard tunnel in October 2001 a traffic management policy has been implemented to limit heavy goods traffic passing through the tunnel, based on the number of cars. This reduces the risk of accidents. In the San Bernadino tunnel, an alternated traffic rule is applied to HGVs - these can pass through the tunnel only in one direction in a given time interval. The Alpine transit fund, set up to help manage reduced traffic capacity across the Alps, is being tested and implemented. There are two models, based on voluntary or compulsory toll systems. An objective of the Swiss Transport policy is to shift as much heavy goods traffic crossing the Alps from road to rail. Means to achieve this goal include the Heavy Vehicle Fee, modernising the railway basic equipment and through railway legal reform. There are two main railways crossing the Alps, through the Gotthard tunnel and the Loetchberg railway tunnel. In addition to the traditional loading of cars/trucks on the train, railway goods transportation is promoted through what is known as combined traffic. This means that goods elements such as container trailers, semi-trailers and trucks are loaded upon the train for long distance travels. Detailed local distribution is then carried out using the road. For the covering abstract see ITRD E139491.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".