Telework and telerehabilitation programs for workers with a stroke during the COVID-19 pandemic: A commentary
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
BACKGROUND: Due to the coronavirus disease 2019 (COVID-19) pandemic, rehabilitation facilities have become less accessible for patients with a stroke. Lack of early, intensive rehabilitation misses the opportunity for recovery during the critical time window of endogenous plasticity and improvement post-stroke. OBJECTIVES: The purpose of this commentary was to highlighting the benefits of telework and telerehabilitation programs for workers with a stroke during the COVID-19 pandemic. METHODS: Relevant publications regarding the management of individuals with a stroke, telerehabilitation and teleworking in the setting of COVID-19 were reviewed. RESULTS: Previous studies showed that telerehabilitation can effectively provide an alternate method of promoting recovery for patients with a stroke. With the physical distancing precautions in place for mitigating viral spread, teleworking can also provide a method for long term recovery and improvements in quality of life after a stroke. CONCLUSIONS: Overall, this commentary addresses the benefits of physically distant, safe and effective alternatives to support individuals who live with a stroke during COVID-19 pandemic.
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