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Record W2088802425 · doi:10.1161/strokeaha.110.596056

Leukoaraiosis and Stroke

2010· review· en· W2088802425 on OpenAlexafffund
Eric E. Smith

Bibliographic record

VenueStroke · 2010
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsOntario Brain Institute
FundersNational Institute of Neurological Disorders and StrokeNational Institute on AgingCanadian Institutes of Health ResearchNational Institutes of HealthHeart and Stroke Foundation of CanadaAlberta InnovatesFondation pour la Recherche MédicaleCanadian Stroke Network
KeywordsLeukoaraiosisMedicineStroke (engine)Cerebral amyloid angiopathyDementiaNeuroimagingLacunar strokeWhite matterCardiologyVascular dementiaVascular diseaseInternal medicineHyperintensityAngiopathyPathologyMagnetic resonance imagingIschemic strokeIschemiaDiseaseRadiologyDiabetes mellitusPsychiatryEndocrinology

Abstract

fetched live from OpenAlex

Leukoaraiosis is a common finding in stroke patients and has been strongly associated with risk of incident stroke and dementia. Leukoaraiosis may also be an independent predictor of stroke outcomes. There is increasing evidence from neuroimaging to support the concept that some leukoaraiosis is caused by white matter infarcts, which may be particularly frequent in patients with aggressive small vessel diseases such as cerebral amyloid angiopathy. The relatively similar distribution of leukoaraiosis regardless of the distribution of vascular pathology suggests a conserved vulnerability to white matter injury across various vascular diseases, possibly related to resting patterns of blood flow. More insights into the pathophysiology of leukoaraiosis are sorely needed to reduce the burden of disability associated with this common condition.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.321
Teacher spread0.288 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
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

Citations138
Published2010
Admission routes2
Has abstractyes

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