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Record W3013671288 · doi:10.1007/s00134-020-06022-5

Surviving Sepsis Campaign: guidelines on the management of critically ill adults with Coronavirus Disease 2019 (COVID-19)

2020· article· en· W3013671288 on OpenAlexaff
Waleed Alhazzani, Morten Hylander Møller, Yaseen M. Arabi, Mark Loeb, Michelle N. Gong, Eddy Fan, Simon Oczkowski, Mitchell M. Levy, Lennie Derde, Amy Dzierba, Bin Du, Michael S. Aboodi, Hannah Wunsch, Maurizio Cecconi, Younsuck Koh, Daniel S. Chertow, Kathryn Maitland, Fayez Alshamsi, Emilie P. Belley‐Côté, Massimiliano Greco, Matthew Laundy, Jill S. Morgan, Jozef Kesecioğlu, Allison McGeer, Leonard A. Mermel, Manoj J. Mammen, Paul Alexander, Amy S. Arrington, John Centofanti, Giuseppe Citerio, Bandar Baw, Ziad A. Memish, Naomi Hammond, Frederick G. Hayden, Laura Evans, Andrew Rhodes

Bibliographic record

VenueIntensive Care Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsPopulation Health Research InstituteSunnybrook Health Science CentreUniversity of TorontoMcMaster UniversityHealth Sciences CentreImpact
Fundersnot available
KeywordsMedicineIntensive care medicineMEDLINEHealth careBest practiceIntensive careAnesthesiologyCoronavirus disease 2019 (COVID-19)Grading (engineering)PandemicCritically illDiseaseMedical emergencyInfectious disease (medical specialty)

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)0.020
metaresearch head score (Gemma)0.056
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.056
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0060.005
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0050.004
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0060.005

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 head0.168
GPT teacher head0.472
Teacher spread0.304 · 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
GenreMethods

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

Citations2,193
Published2020
Admission routes1
Has abstractno

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