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Record W7116748690 · doi:10.1016/j.resplu.2025.101204

Wolf Creek XVIII Part 6: transforming clinical trial design in cardiac arrest research

2025· article· en· W7116748690 on OpenAlexaff
Karen G. Hirsch, Janet Bray, Clifton W. Callaway, Keith Couper, Ian R. Drennan, Theresa Olasveengen, Gavin D Perkins, Jonathan Elmer

Bibliographic record

VenueResuscitation Plus · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsTransport CanadaSunnybrook Health Science Centre
Fundersnot available
KeywordsClinical trialPresentation (obstetrics)Research designAlternative medicinePatient careClinical researchClinical study design

Abstract

fetched live from OpenAlex

The 50th Anniversary Wolf Creek XVIII Conference was hosted by the Max Harry Weil Institute for Critical Care Research and Innovation in Ann Arbor, Michigan, USA on June 19-21, 2025. "Transforming Clinical Trial Design in Cardiac Arrest Research" was a topic of focused presentation and discussion. Participants included invited panelists and conference attendees made up of international academic and industry scientists as well as thought leaders in the field of cardiac arrest resuscitation. Panelists identified six key opportunities to transform clinical trial design: (1) Selecting the "right" patient and intervention, (2) Optimizing randomization, (3) Measuring relevant and unbiased outcomes, (4) Designing alternative approaches to "usual" randomize controlled trials (RCTs), (5) Maintaining public trust and engagement, and (6) Changing the approach to knowledge translation from research into clinical practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.261
metaresearch head score (Gemma)0.222
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score0.911

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2610.222
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0040.006
Scholarly communication0.0210.008
Open science0.0050.011
Research integrity0.0210.023
Insufficient payload (model declined to judge)0.0260.014

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 head0.135
GPT teacher head0.441
Teacher spread0.306 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
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

Citations0
Published2025
Admission routes1
Has abstractyes

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