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Record W2034706957 · doi:10.1080/02699050600744087

Identification of aphasia post stroke: A review of screening assessment tools

2006· review· en· W2034706957 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrain Injury · 2006
Typereview
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsWestern UniversitySt Joseph's Health CentreParkwood Institute
Fundersnot available
KeywordsAphasiaStroke (engine)Identification (biology)MedicinePhysical medicine and rehabilitationPsychologyPsychiatryEngineeringBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Aphasia is one of the most common consequences of stroke. Early identification, diagnosis and treatment of language deficits are important steps in maximizing rehabilitation gains. A routine screening test is an invaluable tool in the identification and appropriate referral of patients with potential communication problems. The present study presents an evaluation of the measurement properties of screening tools for aphasia found within the stroke research literature. METHODS: Screening tools were identified following searches of the published research literature in stroke. Instruments were reviewed on the basis of reliability, validity, classification sensitivity and practical utility. RESULTS: Six aphasia screening tools were identified. For most tools, information pertaining to measurement properties and clinical utility was limited. CONCLUSIONS: The Frenchay Aphasia Screening Test (FAST) appears to be the most widely used and thoroughly evaluated tool found within the stroke research literature. Further evaluation of the measurement properties and clinical utility of screening tools is recommended.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.073
GPT teacher head0.409
Teacher spread0.336 · 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