Case studies: results and synthesis projet 7FP CLOSER (Connecting LOng and Short-distance networks for Efficient Transport) Rapport de recherche Deliverable 5.2 project européen CLOSER.
Bibliographic record
Abstract
The CLOSER project has been set to analyse the interfaces and interconnectionsbetween long distance transport networks and local/regional transport networks of allmodes. The project is funded within the Seventh Framework Programme of theEuropean Commission, under the topic TPT-2008.0.0.13 “New mobility/organisationalschemes: interconnection between short and long-distance transport networks”.The objective of WP5 of CLOSER is to accomplish in-depth case studies to deepenand validate the understanding of results obtained in Work packages 2, 3 and 4. Thiswill be achieved by:- Developing a joint assessment and evaluation framework for the case studies,incorporating knowledge that has been obtained in WP 2, WP 3 and WP 4- Carrying out the case studies- Synthesising the results of the case studies in order to give inputs for thedevelopment of recommendations in WP 6.The deliverable at hand summarises the seven case studies that have been conductedin the CLOSER project: Leipzig-Halle airport (Germany) Armentiéres station (France) Oslo bus terminal Vaterland (Norway) Port of Helsinki (Finland) Thessaloniki port (Greece) Constantza port (Romania) Vilnius Airport (Lithuania)
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".