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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 OpenAlex
Sarah Lee, Prakash Muthusami, Bruce A. Wasserman, Jeremy J. Heit, Ronil V. Chandra, Ferdinand Hui, Matías Negrotto, Todd Abruzzo

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

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.096
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