Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Global Positioning System (GPS)-based travel diaries have emerged as valuable tools for urban transportation planning but have had little uptake in rural transportation planning. This chapter describes the methodology and effectiveness of employing vehicle-instrumented passive GPS units and participant-prompted recall with Geographic Information Systems (GIS) in a rural travel diary study focused on understanding older driver travel behaviour. A convenience sample of 60 rural older drivers in New Brunswick, Canada participated for an average of 5.3 days. The GPS devices recorded 1649 “stops” of 1 minute or more, with 8% of all “stops” due to stoplights or traffic delay. Remaining “stops” were organized into 1494 trips (one origin with one destination), with participants supplying travel purposes and driver and passenger details for 99.1% of trips. An external battery for the GPS unit minimized satellite acquisition delay but was exhausted in 10% of cases. Results from the study permitted an exploratory analysis of the impact of select license restrictions on older drivers, the potential for rural older drivers to meet their needs without a car, and exposure analysis by road class.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it