Mobility routing optimization for physical accessibility and thermoregulation
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
Abstract. As routing applications become common on mobile devices, significant problems that remain are the sparse underlying data support for pedestrian-based routing and the inability to customize an existing route for specific individual accessibility needs. Cartographic researchers have repeatedly demonstrated methods for sophisticated modelling of infrastructure and have built routing portals and accessibility systems, yet these systems and their benefits have not been used widely, due to problems with underlying data support. This research reviews a few exemplar systems and presents a new routing study that uses the presence of overhead tree canopy to add a preference layer to individual routing. This allows individuals to plan and choose navigation pathways for purposes of body heat thermoregulation, a problem that exists for many individuals with mobility impairments, particularly those with spinal cord injuries. The study presented here demonstrates that successful routing underneath the tree canopy can be done in a way that only marginally increases the length of such routes. This study also demonstrates the need for detailed geographic data support for preference-based routing.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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