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Record W2096821867 · doi:10.1177/0883073811408089

The Vascular Effects of Infection in Pediatric Stroke (VIPS) Study

2011· article· en· W2096821867 on OpenAlexaff
Heather J. Fullerton, Mitchell S.V. Elkind, A. James Barkovich, Carol Glaser, David V. Glidden, Nancy K. Hills, Carlos Leiva‐Salinas, Max Wintermark, Gabrielle deVeber

Bibliographic record

VenueJournal of Child Neurology · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsHospital for Sick Children
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of HealthStroke Association
KeywordsMedicineStroke (engine)Pediatric strokeArterial Ischemic StrokeProspective cohort studyCohortIschemic strokeInternal medicineCerebrospinal fluidIschemia

Abstract

fetched live from OpenAlex

Understanding the vascular injury pathway is crucial to developing rational strategies for secondary stroke prevention in children. The multicenter Vascular Effects of Infection in Pediatric Stroke (VIPS) cohort study will test the hypotheses that (1) infection can lead to childhood arterial ischemic stroke by causing vascular injury and (2) resultant arteriopathy and inflammatory markers predict recurrent stroke. The authors are prospectively enrolling 480 children (aged 1 month through 18 years) with arterial ischemic stroke and collecting extensive infectious histories, blood and serum samples (and cerebrospinal fluid, when clinically obtained), and standardized brain and cerebrovascular imaging studies. Laboratory assays include serologies (acute and convalescent) and molecular assays for herpesviruses and levels of inflammatory markers. Participants are followed prospectively for recurrent ischemic events (minimum of 1 year). The analyses will measure association between markers of infection and cerebral arteriopathy and will assess whether cerebral arteriopathy and inflammatory markers predict recurrent stroke.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations79
Published2011
Admission routes1
Has abstractyes

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