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Contemporary aetiologies of medical complexity in children: a cohort study

2022· letter· en· W4312030263 on OpenAlexafffund
Bushra Haque, Tayyaba Khan, Inna Ushcatz, Meredith Curtis, Amy Pan, Wendy Wu, Julia Orkin, Gregory Costain

Bibliographic record

VenueArchives of Disease in Childhood · 2022
Typeletter
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersMedical Research CouncilCanadian Institutes of Health ResearchHospital for Sick ChildrenMcLaughlin Centre, University of TorontoUniversity of TorontoSickkids Research Institute
KeywordsMedicineCohortPediatricsCohort studyFamily medicinePathology

Abstract

fetched live from OpenAlex

with infants without symptoms in the period of 1-14 days post vaccination. CRP among symptomatic children was similar in the period of 1-7 days post vaccination (p=0.81) and marginally higher than asymptomatic infants 8-14 days post vaccination (adjusted mean difference 1.72 mg/L; 95% CI 1.10 to 2.69, p=0.018). Among 2.7% (9/339) infants with CRP of >50 mg/L, none required hospitalisation. Limitations include small samples (particularly 0-14 days prevaccination), selection bias and the range of vaccines.

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 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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0010.009
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 head0.421
GPT teacher head0.501
Teacher spread0.079 · 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 teacher head, not a consensus.

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

Citations16
Published2022
Admission routes2
Has abstractyes

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