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Record W3203065019 · doi:10.1097/rmr.0000000000000272

Definitive Diagnostic Evaluation of the Child With Arterial Ischemic Stroke and Approaches to Secondary Stroke Prevention

2021· review· en· W3203065019 on OpenAlexaff
Sarah Lee, Prakash Muthusami, Bruce A. Wasserman, Jeremy J. Heit, Ronil V. Chandra, Ferdinand Hui, Matías Negrotto, Todd Abruzzo

Bibliographic record

VenueTopics in Magnetic Resonance Imaging · 2021
Typereview
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsStroke (engine)MedicineEtiologyNeuroimagingPediatric strokeSecondary preventionArterial Ischemic StrokeIntensive care medicineIschemic strokeMagnetic resonance imagingPediatricsPhysical therapyPathologyRadiologyCardiologyInternal medicineIschemiaPsychiatry

Abstract

fetched live from OpenAlex

ABSTRACT: In children with arterial ischemic stroke (AIS), the definitive diagnosis of stroke subtype and confirmation of stroke etiology is necessary to mitigate stroke morbidity and prevent recurrent stroke. The common causes of AIS in children are sharply differentiated from the common causes of adult AIS. A comprehensive, structured diagnostic approach will identify the etiology of stroke in most children. Adequate diagnostic evaluation relies on advanced brain imaging and vascular imaging studies. A variety of medical and surgical secondary stroke prevention strategies directed at the underlying cause of stroke are available. This review aims to outline strategies for definitive diagnosis and secondary stroke prevention in children with AIS, emphasizing the critical role of neuroimaging.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.096
GPT teacher head0.318
Teacher spread0.222 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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