Successfully Navigating to Patient Centered Post Stroke and Post TIA Driving Resources
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
Successfully Navigating to Patient Centered Post Stroke & Post TIA Driving Resources Background:Southwestern Ontario is an area with a wide rural geography where driving is essential to everyday living. Following a stroke or Transient Ischemic Attack (TIA), all patients need to be evaluated for their fitness to return to driving. Approximately 50% of those who have had a stroke will return to driving. Understanding and navigating return to driving is confusing and complex. Additionally, those with TIA have difficulty comprehending why they cannot return to driving immediately after their symptoms resolve. Objective:A resource was sought to a) improve patient understanding and navigation for their return to the wheel and b) provide a consistent message for Health Care Providers to utilize when communicating a no-driving message.Methods:An interested group of Occupational Therapists from the Southwestern Ontario Stroke Network (SWOSN) undertook the creation of this resource. This comprehensive iterative process included locating and reviewing provincial and international driving resources from multiple sources as well as consulting legislative documents, experts and professional guidelines. Once a draft was underway patient review and input was sought. Multiple revisions were made to be responsive to all feedback. The document was constructed to be patient centric with headings such as u201cWhat is the process for getting my license back?u201d, u201cWhat happens during a driving assessment?u201d, and u201cWhat if I am no longer able to drive?u201dResults:Two patient centric documents were created; Driving After Stroke in Ontario and Driving After TIA in Ontario. Next Steps:u2022tBroad dissemination across the SWOSN region u2022tStroke survivor and therapist evaluationu2022tIncorporate feedback into future revisions
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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