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Record W3081015435 · doi:10.1016/s2213-2600(20)30366-0

Prevalence of phenotypes of acute respiratory distress syndrome in critically ill patients with COVID-19: a prospective observational study

2020· article· en· W3081015435 on OpenAlexfundno aff
Pratik Sinha, Carolyn S. Calfee, Shiney Cherian, David Brealey, Sean Cutler, Charles C. King, Charlotte Killick, Owen Richards, Yusuf Cheema, Catherine Bailey, Kiran Reddy, Kevin Delucchi, Manu Shankar‐Hari, Anthony Gordon, Murali Shyamsundar, Cecilia O’Kane, Daniel F. McAuley, Tamás Szakmány

Bibliographic record

VenueThe Lancet Respiratory Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
FundersDivision of Financial ManagementNational Heart, Lung, and Blood InstituteNIHR Imperial Biomedical Research CentreInnovate UKQueen's UniversityNational Institutes of HealthDepartment of Health and Social CareChina Scholarship CouncilNational Institute of General Medical SciencesNational Institute for Health and Care ResearchDepartment for Employment and Learning, Northern IrelandWellcome TrustMedical Research CouncilBayerNational Institute on Handicapped ResearchGenentechQueen's University Belfast
KeywordsMedicineObservational studyCoronavirus disease 2019 (COVID-19)Critically illAcute respiratory distressCritical illnessSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakIntensive care medicineARDSSeverity of illnessRespiratory distressProspective cohort studyDistressPandemicBetacoronavirusMEDLINEEmergency medicineInternal medicineVirologyOutbreakLungDiseaseSurgery

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.098
GPT teacher head0.348
Teacher spread0.250 · 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.

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

Citations267
Published2020
Admission routes1
Has abstractno

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