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Record W3014859092 · doi:10.1097/pcc.0000000000002376

Coronavirus Disease 2019 in Critically Ill Children: A Narrative Review of the Literature*

2020· review· en· W3014859092 on OpenAlexaff
Jacqueline Soo May Ong, Alvise Tosoni, Yae‐Jean Kim, Niranjan Kissoon, Srinivas Murthy

Bibliographic record

VenuePediatric Critical Care Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineIntensive care medicineCritically illPreparednessCoronavirus disease 2019 (COVID-19)DiseaseNarrative reviewRelevance (law)Coronavirus2019-20 coronavirus outbreakCritical illnessMEDLINEDisease managementSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Infectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

Coronavirus disease 2019 has spread around the world. In the 3 months since its emergence, we have learned a great deal about its clinical management and its relevance to the pediatric critical care provider. In this article, we review the available literature and provide valuable insight into the clinical management of this disease, as well as information on preparedness activities that every PICU should perform.

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)0.000
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.780
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.045
GPT teacher head0.405
Teacher spread0.359 · 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 designSystematic review
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

Citations87
Published2020
Admission routes1
Has abstractyes

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