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Record W2000573880 · doi:10.1310/g8pk-r5ef-bmay-kt5t

Research Gaps in Stroke Rehabilitation

2003· review· en· W2000573880 on OpenAlexaff
Robert Teasell, Jeffrey W. Jutai, Sanjit K. Bhogal, Norine Foley

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2003
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsSt Joseph's Health CareWestern University
Fundersnot available
KeywordsRehabilitationStroke (engine)Physical medicine and rehabilitationMedicinePhysical therapyPsychologyEngineering

Abstract

fetched live from OpenAlex

The Stroke Rehabilitation Evidence-Based Review was designed to be a comprehensive review of the stroke rehabilitation literature. Despite a wealth of research, which included 272 randomized controlled trials (RCTs), many research questions remained unanswered. In the absence of strong evidence (at least two RCTs confirming the efficacy of a treatment), a research gap was identified. These gaps, in areas of research rehabilitation research considered to be of clinical significance, are presented in this article as unanswered research questions.

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)0.072
metaresearch head score (Gemma)0.143
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0720.143
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.004
Bibliometrics0.0140.017
Science and technology studies0.0020.004
Scholarly communication0.0090.015
Open science0.0030.005
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0080.002

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 head0.068
GPT teacher head0.430
Teacher spread0.362 · 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 designNot applicable
DomainEvaluation
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

Citations16
Published2003
Admission routes1
Has abstractyes

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