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Barriers to Goals of Care Discussions With Patients Who Have Advanced Heart Failure: Results of a Multicenter Survey of Hospital-Based Cardiology Clinicians

2017· article· en· W2709090053 on OpenAlexaff
John J. You, Natasha Aleksova, Anique Ducharme, Jane MacIver, Lisa Mielniczuk, Robert Fowler, Catherine Demers, Brian Clarke, Marie-Claude Parent, Mustafa Toma, Patricia H. Strachan, Paul Farand, Debra Isaac, Shelley Zieroth, Marilyn Swinton, Xuran Jiang, Andrew G. Day, Daren K. Heyland, Heather J. Ross

Bibliographic record

VenueJournal of Cardiac Failure · 2017
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsQueen's UniversityClinical Evaluation Research UnitUniversity of ManitobaSt. Boniface HospitalKingston General HospitalUniversity of CalgarySt. Paul's HospitalUniversity of OttawaHôpital du Sacré-Cœur de MontréalImpactNova Scotia Health AuthorityUniversité de MontréalQueen Elizabeth II Health Sciences CentreUniversity of British ColumbiaMontreal Heart InstituteMcMaster UniversityDalhousie UniversityUniversité de SherbrookeUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineHeart failureMulticenter studyCardiologyInternal medicineIntensive care medicineFamily medicineEmergency medicineRandomized controlled trial

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)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.294
Teacher spread0.283 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations51
Published2017
Admission routes1
Has abstractno

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