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Record W2041732571 · doi:10.1310/y6tg-1kq9-ledq-64l8

Stroke Rehabilitation Evidence-Based Review: Methodology

2003· article· en· W2041732571 on OpenAlexafffund
Norine Foley, Robert Teasell, Sanjit K. Bhogal, Mark Speechley

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2003
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsWestern UniversitySt Joseph's Health CareParkwood Institute
FundersHeart and Stroke Foundation of Canada
KeywordsRehabilitationStroke (engine)Physical medicine and rehabilitationMedicinePsychological interventionRandomized controlled trialPhysical therapyPsychiatrySurgery

Abstract

fetched live from OpenAlex

The Stroke Rehabilitation Evidence-Based Review was intended to be an up-to-date review of all therapies associated with stroke rehabilitation including both therapeutic interventions and medications. This section describes the literature search strategy, the data abstraction process, and the scale used to evaluate the methodological quality of randomized controlled trials included in the review and the system upon which the levels of evidence were based.

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)0.109
metaresearch head score (Gemma)0.217
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.576

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.217
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0220.013
Bibliometrics0.0360.039
Science and technology studies0.0030.003
Scholarly communication0.0090.005
Open science0.0070.007
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0310.005

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 head0.078
GPT teacher head0.377
Teacher spread0.299 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainMethods
GenreReview

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

Citations390
Published2003
Admission routes2
Has abstractyes

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