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European Resuscitation Council Guidelines 2025 Executive Summary

2025· article· en· W4415407823 on OpenAlexaff
Robert Greif, Kasper Glerup Lauridsen, Therese Djärv, Jacqueline Eleonora Ek, Vix Monnelly, Koenraad G. Monsieurs, Νικόλαος Νικολάου, Theresa M. Olasveengen, Federico Semeraro, Anastasia Spartinou, Joyce Yeung, Enrico Baldi, Dominique Biarent, Jana Djakow, Sander van Goor, Jan‐Thorsten Gräsner, Marije Hogeveen, Vlasios Karageorgos, Carsten Lott, John Madar, Sabine Nabecker, Timo de Raad, Violetta Raffay, Jessica Rogers, Claudio Sandroni, Sebastian Schnaubelt, Michael A. Smyth, Jasmeet Soar, Johannes Wittig, Gavin D. Perkins, Jerry P. Nolan

Bibliographic record

VenueResuscitation · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsSinai Health SystemUniversity of Toronto
FundersEuropean Research CouncilLaerdal Foundation for Acute Medicine
KeywordsResuscitationExecutive summaryAdvanced life supportCardiopulmonary resuscitationBasic life supportLegislationGuidelineChain of survivalMEDLINE

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)0.017
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: Review · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.056
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.005
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0040.003
Research integrity0.0110.007
Insufficient payload (model declined to judge)0.0410.030

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 head0.051
GPT teacher head0.326
Teacher spread0.275 · 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

Citations40
Published2025
Admission routes1
Has abstractno

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