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Record W2345775441 · doi:10.1017/cem.2016.26

What is new in the 2015 American Heart Association guidelines, what is recycled from 2010, and what is relevant for emergency medicine in Canada

2016· article· en· W2345775441 on OpenAlexafffundabout
Laurie J. Morrison, Allan de Caen, Farhan Bhanji, Blair L. Bigham, Ian E. Blanchard, Steven C. Brooks, Anne‐Marie Guerguerian, Jan L. Jensen, Andrew H. Travers, Christian Vaillancourt, Michelle Welsford, Karen Woolfrey

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsOttawa HospitalDalhousie UniversityUniversity of CalgaryQueen's UniversitySickKids FoundationAlberta Health ServicesMcMaster UniversityHospital for Sick ChildrenStollery Children's HospitalUniversity of OttawaMcGill University Health CentreUniversity of AlbertaSt. Michael's HospitalWestern UniversityUniversity of Toronto
FundersHeart and Stroke Foundation of CanadaAmerican Heart Association
KeywordsMedicineAssociation (psychology)Action (physics)Call to actionMedical emergencyInternet privacyAdvertisingBusinessComputer science

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)0.016
metaresearch head score (Gemma)0.080
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 score0.069
Threshold uncertainty score0.502

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.008
Science and technology studies0.0060.007
Scholarly communication0.0150.008
Open science0.0040.003
Research integrity0.0070.015
Insufficient payload (model declined to judge)0.0080.001

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 head0.054
GPT teacher head0.349
Teacher spread0.295 · 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
Published2016
Admission routes3
Has abstractno

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