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Record W2046002848 · doi:10.1007/s00134-010-1759-y

Recommendations for intensive care unit and hospital preparations for an influenza epidemic or mass disaster: summary report of the European Society of Intensive Care Medicine’s Task Force for intensive care unit triage during an influenza epidemic or mass disaster

2010· review· en· W2046002848 on OpenAlexaff
Charles L. Sprung, Janice L. Zimmerman, Gavin M. Joynt, John L. Hick, Bruce Taylor, Guy A. Richards, Christian Sandrock, Robert Cohen, Bruria Adini

Bibliographic record

VenueIntensive Care Medicine · 2010
Typereview
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
FundersNIH Clinical CenterSchool of Medicine and Public Health, University of Wisconsin-MadisonUniversity of California, San DiegoWeill Cornell Medical CollegePeking University People's HospitalUniversitat Autònoma de BarcelonaPeking UniversityUniversitat de BarcelonaNational Institutes of HealthChinese University of Hong KongBritish Infection SocietyUniversity of WashingtonImperial College LondonImperial College Healthcare NHS TrustEuropean Society of Clinical Microbiology and Infectious DiseasesIntensive Care SocietyAmerican Thoracic SocietyUniversity College LondonHennepin County Medical Center
KeywordsMedicineTriagePreparednessMedical emergencyIntensive care unitIntensive carePersonal protective equipmentDelphi methodInfection controlIntensive care medicineCoronavirus disease 2019 (COVID-19)

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 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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.206
GPT teacher head0.485
Teacher spread0.279 · 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 designNot applicable
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

Citations166
Published2010
Admission routes1
Has abstractno

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