Bibliographic record
Abstract
The amount of travel by car is increasing, leading to a range of problems. According to the National Travel Survey (NTS) (Department of the Environment, Transport and the Regions, 1999) a quarter of all car trips are less than two miles long and more than half are less than five miles. This paper presents some of the findings from a project entitled 'Potential for mode transfer of short trips'. Some preliminary results have been presented previously (Mackett, 1999) (ITRD E104616). The project has been carried out in the Centre for Transport Studies at University College London (UCL) in partnership with Steer Davies Gleave (SDG) for DETR. The overall objective of the work was to contribute to Government policy to encourage the use of the environmentally-benign travel modes in order to reduce the amount of travel by private car. The focus was on the encouragement of the use of walking, cycling and public transport (buses in particular). The focus of this work is 'short trips'. In this work these are usually taken to be those of less than 5 miles (8 kilometres). (A) For the covering abstract see ITRD E107063.
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 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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".