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Record W2077160103 · doi:10.1310/31pk-d1j8-1fbn-0k3k

Quality of the Stroke Rehabilitation Research

2003· article· en· W2077160103 on OpenAlexaff
Sanjit K. Bhogal, Robert Teasell, Norine Foley, Mark Speechley

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2003
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsWestern UniversitySt Joseph's Health CareParkwood Institute
Fundersnot available
KeywordsRehabilitationBlindingStroke (engine)Physical medicine and rehabilitationPhysical therapyMedicineQuality (philosophy)PsychologyRandomized controlled trialSurgery

Abstract

fetched live from OpenAlex

The Stroke Rehabilitation Evidence-Based Review revealed a wide range of quality scores across primary studies. The aim of this section is to determine what differences there are across studies and to provide a detailed examination of methodological issues in the stroke rehabilitation literature. Methodology of each article was assessed using the Physiotherapy Evidence Database (PEDro) quality scale. Mean PEDro scores and percentage of studies meeting individual PEDro criteria were determined for all studies, for therapy-based studies only, and for drug-based studies only. It was noted that the stroke rehabilitation literature lacked rigor in the area of concealed allocation, blinding of the assessor, and intention-to-treat analysis. Investigation of the methodological quality of stroke rehabilitation literature emphasizes the need for improved treatment protocols, taking into account previous deficits, during research.

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 imitation

Not 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.

metaresearch head score (Codex)0.337
metaresearch head score (Gemma)0.607
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score0.818

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3370.607
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0100.009
Bibliometrics0.0340.038
Science and technology studies0.0020.003
Scholarly communication0.0130.005
Open science0.0040.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.062
GPT teacher head0.405
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
GenreEmpirical

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".

Quick stats

Citations9
Published2003
Admission routes1
Has abstractyes

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