Bibliographic record
Abstract
More than 13 million cases of stroke are occurring annually worldwide. Approximately a quarter of these strokes are recurrent strokes, and there is compelling evidence of the benefit of supervised exercise and risk factor modification programming in the secondary prevention of these strokes. However, there is insufficient time in inpatient and outpatient stroke rehabilitation for focused exercise interventions. General lifestyle interventions on their own, without guidance and supervision, are insufficient for improving physical activity levels. Cardiac rehabilitation (CR) is a setting where cardiac patients, and increasingly stroke patients, receive comprehensive secondary prevention programming, including structured exercise. Unfortunately, not all CR programs accept referrals for people following a stroke and for those that do, only a few patients participate. Therefore, the purpose of this review is to report the barriers and facilitators to improving linkage between health services, with a focus on increasing access to CR. In the next two decades, it is projected that there will be a marked increase in stroke prevalence globally. Therefore, there is an urgent need to create cross-program collaborations between hospitals, outpatient stroke rehabilitation, CR, and community programs. Improving access and removing disparities in access to evidence-based exercise treatments would positively affect the lives of millions of people recovering from stroke.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".