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Record W3203103016 · doi:10.1097/ccm.0000000000005337

Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021

2021· article· en· W3203103016 on OpenAlexafffund
Laura Evans, Andrew Rhodes, Waleed Alhazzani, Massimo Antonelli, Craig M. Coopersmith, Craig French, Flávia Ribeiro Machado, Lauralyn McIntyre, Marlies Ostermann, Hallie C. Prescott, Christa Schorr, Steven Q. Simpson, W. Joost Wiersinga, Fayez Alshamsi, Derek C. Angus, Yaseen M. Arabi, Luciano César Pontes Azevedo, Richard Beale, Gregory J. Beilman, Emilie P. Belley‐Côté, Lisa Burry, Maurizio Cecconi, John Centofanti, Angel Coz Yataco, Jan J. De Waele, R. Phillip Dellinger, Kent Doi, Bin Du, Elisa Estenssoro, Ricard Ferrer, Charles D. Gomersall, Carol Hodgson, Morten Hylander Møller, Theodore J. Iwashyna, Shevin T. Jacob, Ruth Kleinpell, Michael Klompas, Younsuck Koh, Anand Kumar, Arthur Kwizera, Suzana Margareth Lobo, Henry Masur, Steven McGloughlin, Sangeeta Mehta, Yatin Mehta, Mervyn Mer, Mark Nunnally, Simon Oczkowski, Tiffany M. Osborn, Elizabeth Papathanassoglou, Anders Perner, Michael A. Puskarich, Jason A. Roberts, William D. Schweickert, Maureen A. Seckel, Jonathan Sevransky, Charles L. Sprung, Tobias Welte, Janice L. Zimmerman, Mitchell M. Levy

Bibliographic record

VenueCritical Care Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsOttawa HospitalUniversity of ManitobaMount Sinai HospitalUniversity of AlbertaPopulation Health Research InstituteMcMaster University
FundersMedical Research CouncilNational Institutes of HealthDansk Selskab for Anæstesiologi og Intensiv MedicinGrifolsEuropean Society of Intensive Care MedicineShionogiUniversiteit GentIsrael Science FoundationFonds Wetenschappelijk OnderzoekIntensive Care SocietyBundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchInsmedMedicines CompanyMcMaster UniversitySocietà Italiana Anestesia, Analgesia, Rianimazione e Terapia IntensivaEdwards LifesciencesAstellas PharmaMarcus FoundationBrown UniversityNational Health and Medical Research CouncilAstraZenecaVlaamse regeringInfectious Diseases Society of AmericaSociety of Hospital Pharmacists of AustraliaCytoSorbents EuropeAmerican Association of Colleges of PharmacyDeutsche ForschungsgemeinschaftSociety for Academic Emergency MedicineSociety of Critical Care AnesthesiologistsGilead SciencesEuropean Respiratory SocietyPfizerAmerican College of Emergency PhysiciansWorld Health Organization
KeywordsMedicineSeptic shockSurviving Sepsis CampaignSepsisIntensive care medicineSevere sepsisShock (circulatory)Internal medicine

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.019
metaresearch head score (Gemma)0.070
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: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.070
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0100.008
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0060.005
Research integrity0.0090.015
Insufficient payload (model declined to judge)0.0300.033

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 head0.153
GPT teacher head0.447
Teacher spread0.294 · 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

Citations2,764
Published2021
Admission routes2
Has abstractyes

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