MétaCan
Menu
Back to cohort
Record W3016555942 · doi:10.1007/s00134-017-4683-6

Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016

2017· article· en· W3016555942 on OpenAlexafffund
Andrew Rhodes, Laura Evans, Waleed Alhazzani, Mitchell M. Levy, Massimo Antonelli, Ricard Ferrer, Anand Kumar, Jonathan Sevransky, Charles L. Sprung, Mark Nunnally, Bram Rochwerg, Gordon D. Rubenfeld, Derek C. Angus, Djillali Annane, Richard Beale, Geoffrey J. Bellinghan, Gordon R. Bernard, Jean‐Daniel Chiche, Craig Coopersmith, Daniel De Backer, Craig French, Seitaro Fujishima, Herwig Gerlach, Jorge Hidalgo, Steven M. Hollenberg, Alan E. Jones, Dilip R. Karnad, Ruth Kleinpell, Koh Y, Thiago Lisboa, Flávia Ribeiro Machado, John J. Marini, John C. Marshall, John E. Mazuski, Lauralyn McIntyre, Anthony S. McLean, Sangeeta Mehta, Rui P. Moreno, John Myburgh, Paolo Navalesi, Osamu Nishida, Tiffany M. Osborn, Anders Perner, Colleen M. Plunkett, Marco Ranieri, Christa Schorr, Maureen A. Seckel, Christopher W. Seymour, Lisa Shieh, Khalid Shukri, Steven Q. Simpson, Mervyn Singer, Bruce Thompson, Sean R. Townsend, T. van der Poll, Jean‐Louis Vincent, W. Joost Wiersinga, Janice L. Zimmerman, R. Phillip Dellinger

Bibliographic record

VenueIntensive Care Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsSt. Michael's HospitalMount Sinai HospitalHealth Sciences CentreSunnybrook Health Science CentreOttawa HospitalUniversity of ManitobaMcMaster University
FundersNational Institute of General Medical SciencesAbbott DiagnosticsAllerganCenters for Disease Control and PreventionGrifolsEuropean Society of AnaesthesiologyIntensive Care SocietyAmerican College of Emergency PhysiciansJapanese Respiratory SocietyCanadian Blood ServicesGordon and Betty Moore FoundationSocietà Italiana Anestesia, Analgesia, Rianimazione e Terapia IntensivaSociety of Critical Care AnesthesiologistsCSL BehringSociety of Hospital MedicineEuropean Respiratory SocietyAmerican Heart AssociationAmerican Thoracic SocietyPfizerAmerican College of SurgeonsUniversiteit van AmsterdamEuropean Society of Intensive Care MedicineEuropean Society of Clinical Microbiology and Infectious DiseasesSociety for Academic Emergency MedicineAmerican Association of Critical-Care Nurses
KeywordsMedicineSeptic shockAnesthesiologySurviving Sepsis CampaignPain medicineSepsisIntensive care medicineShock (circulatory)Severe sepsisMedical emergencyEmergency medicineSurgeryAnesthesiaInternal medicine

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)0.014
metaresearch head score (Gemma)0.033
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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.033
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0080.007
Science and technology studies0.0010.002
Scholarly communication0.0050.002
Open science0.0040.004
Research integrity0.0050.016
Insufficient payload (model declined to judge)0.0040.004

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 head0.164
GPT teacher head0.432
Teacher spread0.269 · 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

Citations6,775
Published2017
Admission routes2
Has abstractno

Explore more

Same venueIntensive Care MedicineSame topicSepsis Diagnosis and TreatmentFrench-language works237,207