Driving Post Stroke in Mississauga, Ontario u2013 An Organizational Effort to Standardize
Bibliographic record
Abstract
Trillium Health Partners is the regional stroke centre in Mississauga, Ontario and as a leader in stroke care it is imperative to provide our patients with the information they require for their recovery and quality of life. Using Canadian Medical Association guidelines, Ministry of Transportation of Ontario standards and Canadian Stroke Best Practice recommendations, organizational post stroke driving standards were developed. A patient information brochure u201cDriving After a Strokeu201d was created; a standardized process of reporting to the MTO was developed; u2018Canned Textu2019 standardized paragraphs about driving restrictions were created and provided to physicians for use in their discharge summaries; and education on the process of returning to driving after stroke was delivered to stakeholders. Chart audits were completed pre and post implementation to measure success and ensure use of new procedures. This quality improvement initiative provides clinicians with greater awareness of their obligations regarding reporting to the MTO and improves organizational adherence to Canadian Medical Association guidelines, Ministry of Transportation Ontario and Canadian Stroke Best Practice guidelines. It has lead other organizations to facilitate similar projects within their regions. Most importantly, this work has improved patient understanding of their own medical-legal restrictions for driving post stroke.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".