Review: providing information improves subjective outcomes but may not improve clinical outcomes in patients with stroke or their carersCommentary
Bibliographic record
Abstract
J Smith Mrs J Smith, Temple Bank House, Bradford Royal Infirmary, Bradford, UK; jane.smith@bradfordhospitals.nhs.uk Can interventions that provide information improve outcomes for patients with stroke or their carers? Studies selected compared information interventions intended to improve patient or carer outcomes with standard care in patients with stroke or transient ischaemic attack (TIA) and their carers. Trials that compared information and another treatment with the other treatment alone were also included. Trials were excluded if information was only 1 component of a more complex rehabilitation intervention. Outcomes included mood (eg, depression or anxiety), activities of daily living, quality of life, service use, and death. Cochrane Stroke Group Trials Register (May 2007); Medline, CINAHL, EMBASE/Excerpta Medica, PsycINFO, Science Citation Index and Social …
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How this classification was reachedexpand
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".